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Theory Seminars and Meetings
STAR Seminar and Other Talks
The Theory Group and those interested in Theory topics meet once a week
for the STAR (Seminar on Theory, Algorithms and cRyptography Research) seminar.
In the Winter-2008 quarter, we are meeting
once a week on Wednesday, 10:00am, in EBU3b 4109 (see webpage). Apart from the
STAR seminar, there are talks given by visiting researchers. Here is
the schedule for these talks.
Speaker
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Time and Location
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Topic and Abstract
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Todor Ristov, CSE, UCSD
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Wed., Feb. 27, 2008, 10am-11pm, CSE 4109
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Topic: Predicate Encryption Supporting Disjunctions, Polynomial Equations, and Inner Products - by Jonathan Katz, Amit Sahai and Brent Waters
Abstract:
References: http://eprint.iacr.org/2007/404
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Daniele Micciancio, CSE, UCSD
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Wed., Feb. 20, 2008, 10am-11pm, CSE 4109
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Topic: SWIFFT: a modest proposal for FFT hashing
Abstract: We propose SWIFFT, a collection of compression functions that are
highly parallelizable and admit very efficient implementations on
modern microprocessors. The main technique underlying our functions
is a novel use of the Fast Fourier Transform (FFT) to achieve
``diffusion,'' together with a linear combination to achieve
compression and ``confusion.'' We provide a detailed security
analysis of concrete instantiations, and give a high-performance
software implementation that exploits the inherent parallelism of the
FFT algorithm. The throughput of our implementation is competitive
with that of SHA-256, with additional parallelism yet to be exploited.
Our functions are set apart from prior proposals (having comparable
efficiency) by a supporting asymptotic security proof: it can
be formally proved that finding a collision in a randomly-chosen
function from the family (with noticeable probability) is at least as
hard as finding short vectors in cyclic/ideal lattices in the
worst case.
[Joint work with Lyubashevsky, Peikert and Rosen (FSE 2008)]
References:
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Petros Mol, CSE, UCSD
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Wed., Feb. 13, 2008, 10am-11pm, CSE 4109
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Topic: Recovering NTRU Secret Key From Inversion Oracles
Abstract: We consider the NTRU encryption scheme as lately suggested for use, and
study the connection between inverting the NTRU primitive
(i.e., the one-way function over the message and the blinding
information which underlies the NTRU scheme) and recovering the NTRU
secret key (universal breaking). We model the inverting algorithms as
black-box oracles and do not take any advantage of the internal ways
by which the inversion works (namely, it does not have to be done by
following the standard decryption algorithm). This allows for secret key
recovery directly from the output on several inversion queries even in
the absence of decryption failures. Our oracles might be queried on both
valid and invalid challenges e, however they are not required to reply
(correctly) when their input is invalid.
We show that key recovery can be reduced to inverting the NTRU function.
The efficiency of the reduction highly depends on the specific values of
the parameters. As a side-result, we connect the collisions of the NTRU
function with decryption failures which helps us gain a deeper insight
into the NTRU primitive.
(Joint work with Moti Yung, to be presented at PKC 2008)
References:
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Vadim Lyubashevsky, CSE, UCSD
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Wed., Feb. 6, 2008, 10am-11pm, CSE 4109
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Topic: Lattice-Based Identification Schemes Secure Under Active Attacks
Abstract: There is an inherent difficulty in building 3-move identification schemes based
on combinatorial problems without much algebraic structure. A
consequence of this is that most standard identification protocols today are
based on the hardness of number theory problems. Not having schemes
based on alternate assumptions is a cause for concern since improved
number theoretic algorithms or the realization of quantum computing
would make the known schemes insecure. In this work, we examine the
possibility of creating identification
protocols based on the hardness of lattice problems. We construct a
3-move identification scheme whose security is based on the
worst-case hardness of the shortest vector problem in all lattices,
and also present a more efficient version based on the hardness of
the same problem in all \emph{cyclic} lattices.
References:
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Kristin Lauter, Microsoft Research
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Wed. Jan. 30, 2008, 10am, CSE 4109
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Topic: Cryptographic hash functions from expander graphs
Abstract: We propose constructing provable collision resistant hash functions from
expander graphs. As examples, we investigate two specific families of optimal
expander graphs for provable hash function constructions: the families of
Ramanujan graphs constructed by Lubotzky-Phillips-Sarnak and Pizer
respectively. When the hash function is constructed from one of Pizer's
Ramanujan graphs, (the set of supersingular elliptic curves over GF(p^2)
with l-isogenies, l a prime different from p), then collision resistance
follows from hardness of computing isogenies between supersingular elliptic
curves. We estimate the cost per bit to compute these hash functions, and we
implement our hash function for several members of the LPS graph family and
give actual timings.
(Joint work with D. Charles and E. Goren.)
References:
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Jean Monnerat, CSE, UCSD
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Wed. Jan. 23, 2008, 10am, CSE 4109
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Topic: Separation Results on the ``One-More'' Computational Problems
Abstract: In 2001, Bellare, Namprempre, Pointcheval and Semanko introduced the
notion of ``one-more'' computational problems. Since their
introduction, these problems have found numerous applications in
cryptography. For instance, Bellare et al. showed how they lead
to a proof of security for Chaum's RSA-based blind signature scheme in
the random oracle model.
In this paper, we provide separation results for the computational
hierarchy of a large class of algebraic ``one-more'' computational
problems (e.g. the one-more discrete logarithm problem, the
one-more RSA problem and the one-more static Computational
Diffie-Hellman problem in a bilinear setting). We also give some
cryptographic implications of these results and, in particular, we
prove that it is very unlikely, that one will ever be able to prove
the unforgeability of Chaum's RSA-based blind signature scheme under
the sole RSA assumption.
(Joint work with Emmanuel Bresson, Jean Monnerat, Damien Vergnaud.
To appear in CT-RSA 2008.)
References:
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Scott Yilek, CSE, UCSD
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Wed., Jan. 16, 2008, 10am-11pm, CSE 4109
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Topic: Chosen-Ciphertext Secure Proxy Re-Encryption --by Canetti and Hohenberger
Abstract: In a proxy re-encryption (PRE) scheme, a proxy is given special information that allows it to translate a ciphertext under one key into a ciphertext of the same message under a different key. The proxy cannot, however, learn anything about the messages encrypted under either key. PRE schemes have many practical applications, including distributed storage, email, and DRM. Previously proposed re-encryption schemes achieved only semantic security; in contrast, applications often require security against chosen ciphertext attacks. We propose a definition of security against chosen ciphertext attacks for PRE schemes, and present a scheme that satisfies the definition. Our construction is efficient and based only on the Decisional Bilinear Diffie-Hellman assumption in the standard model. We also formally capture CCA security for PRE schemes via both a game-based definition and simulation-based definitions that guarantee universally composable security. We note that, simultaneously with our work, Green and Ateniese proposed a CCA-secure PRE, discussed herein.
References: http://doi.acm.org/10.1145/1315245.1315269
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Kirill Levchenko, CSE, UCSD
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Wed., Dec. 5, 2007, 11am-12pm, CSE 4109
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Topic: The Synergy between Systems and Theory: How Theory Can Benefit From Systems and Networking.
Abstract:
References:
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Chris Peikert, SRI International
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Wed., Nov. 21, 2007, 11am-12pm, CSE 4109
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Topic: Lossy Trapdoor Functions and Their Applications
Abstract: We propose a new general primitive called *lossy trapdoor functions*
(lossy TDFs), and realize it under a variety of different
number theoretic assumptions, including hardness of the decisional
Diffie-Hellman (DDH) problem and the *worst-case* hardness of
standard lattice problems.
Using lossy TDFs, we develop a new approach for constructing many
important cryptographic primitives, including standard trapdoor
functions, CCA-secure cryptosystems, and more. All of the constructions
are simple, efficient, and black-box.
Taken all together, these results resolve some long-standing open
problems in cryptography. They give the first known (injective)
trapdoor functions that are not directly related to integer
factorization, and provide the first known CCA-secure cryptosystem
based solely on worst-case lattice assumptions.
Joint work with Brent Waters of SRI International.
References:
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Scott Yilek, CSE, UCSD
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Wed., Nov. 14, 2007, 11am-12pm, CSE 4109
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Topic: The Round-Complexity of Black-Box Zero-Knowledge: A Combinatorial Characterization
Abstract: The round-complexity of black-box zero-knowledge
has for years been a topic of much interest.
Results in this area generally focus on either
proving lower bounds in various settings (e.g.,
Canetti, Kilian, Petrank, and Rosen prove
concurrent zero-knowledge (cZK) requires
Omega(log n / loglog n) rounds of interaction),
or giving upper bounds (e.g., Prabhakaran, Rosen,
and Sahai give a cZK protocol with omega(log n)
rounds).
We show that though proving upper
bounds seems to be quite different from
demonstrating lower bounds, underlying both tasks
there is in fact a single, simple combinatorial
game between two players which we call the
rewinder and the scheduler. We give two theorems
relating the success of rewinders in the game to
both upper and lower bounds for black-box
zero-knowledge in various settings (single-session,
concurrent composition, etc). Our game and
theorems unify the previous results in the area
while greatly simplifying the task of proving
upper and lower bounds, and should be useful in
showing future results.
(Joint work with Daniele Micciancio, to be presented at TCC 2008)
References:
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Vadim Lyubashevsky, CSE, UCSD
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Wed., Nov. 7, 2007, 11am-12pm, CSE 4109
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Topic: Asymptotically Efficient Lattice-Based Digital Signatures
Abstract: We give a direct construction of digital signatures based on the
complexity of approximating the shortest vector in ideal (e.g.,
cyclic) lattices. The construction is provably secure based on the
worst-case hardness of approximating the shortest vector in such
lattices within a polynomial factor, and it is also asymptotically
efficient: the time complexity of the signing and verification
algorithms, as well as key and signature size is almost linear (up
to poly-logarithmic factors) in the dimension $n$ of the underlying
lattice. Since no sub-exponential (in n) time algorithm is known
to solve lattice problems in the worst case, even when restricted to
cyclic lattices, our construction gives a digital signature scheme
with an essentially optimal performance/security trade-off.
(Joint work with Daniele Micciancio, to be presented at TCC 2008)
References:
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Alexander Vardy, UCSD
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Wed., Oct. 31, 2007, 11am-12pm, CSE 4109
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Topic: Multivariate Interpolation Decoding: Reaching the Ultimate Limit of List Error-Correction
Abstract: One of the central questions in coding theory is this: What is
the largest possible fraction of errors that a code of rate R can
correct? We consider the case of adversarial errors, with error-
correction defined in the list-decoding sense. Due to a series of
ground-breaking papers in the past decade, we now have a complete
answer to this question: the ultimate error-correction radius of
1 - R can be reached and, moreover, this can be done constructively
with polynomial-time decoding.
These exciting results will be presented in the chronological
order of their development. We'll start with a brief introduction to
Reed-Solomon codes and their decoding based on bivariate polynomial
interpolation. This method, developed by Sudan and Guruswami-Sudan
in the late 1990s, achieves a list-decoding radius of 1 - \sqrt{R},
improving upon the classical (1-R)/2 bound. We'll then devise a new
decoding algorithm for Reed-Solomon codes based upon M-variate
polynomial interpolation. The first nontrivial case M = 3 will be
discussed in detail. We will show that, in contrast to the bivariate
case, the recovery of the transmitted message requires at least *two*
trivariate polynomials that satisfy the interpolation constraints.
This will force us to part ways with Reed-Solomon codes, and introduce
a new family of nonlinear algebraic codes that are list-decodable
beyond the Guruswami-Sudan bound of 1 - \sqrt{R}. The key idea is to
combine multivariate interpolation decoding with a kind of "inverted"
algebraic-geometric construction. That is, instead of evaluating
certain functions at rational points of a curve, we evaluate the
rational points *themselves*, viewed as pairs of polynomials over
a subfield, at certain elements of the subfield. This construction
leads to polynomial-time error-correction up to the radius of
1 - O(R log(1/R)). Finally, we will review the recent preprint of
Guruswami and Rudra, which shows how this construction can be combined
with a clever folding technique in order to list-decode up to the
radius of 1 - R - \epsilon, for any positive \epsilon.
References:
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Wenbo Zhao, UCSD
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Wed., Oct. 17, 2007, 11am-12pm, CSE 4109
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Topic: Analysis of Greedy Approximation with Nonsubmodular Potential Function
Abstract: In recent work of Du, Graham, Pardalos, Wan, Wu and Zhao, we introduced a
new method which can analyze a large class of greedy approximations with
non-submodular potential functions, including some long-standing heuristics
for Steiner trees, connected dominating sets, and power assignment in wireless
networks. There exist many greedy approximations for various combinatorial
optimization problems, such as set covering, Steiner tree,
subset-interconnection designs, etc. There are also many methods to analyze
these in the literature. However, all of the previously known methods are
suitable only for those greedy approximations with submodular potential
functions.
This talk is based on joint work with D.-Z. Du, R. L. Graham, P. M. Pardalos,
P.-J. Wan and W. Wu to be presented at SODA 2008.
References:
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Tom Ristenpart, CSE, UCSD
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Wednesday, October 10, 2007, 11am-12pm, CSE 4109
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Topic: How to build a hash function from any collision-resistant function
Abstract: Recent collision-finding attacks against hash functions such
as MD5 and SHA-1 motivate the use of provably collision-resistant (CR)
functions in their place. Finding a collision in a provably CR function
implies the ability to solve some hard problem (e.g., factoring). Unfor-
tunately, existing provably CR functions make poor replacements for
hash functions as they fail to deliver behaviors demanded by practi-
cal use. In particular, they are easily distinguished from a random ora-
cle. We initiate an investigation into building hash functions from prov-
ably CR functions. As a method for achieving this, we present the Mix-
Compress-Mix (MCM) construction; it envelopes any provably CR func-
tion H (with suitable regularity properties) between two injective “mix-
ing” stages. The MCM construction simultaneously enjoys (1) provable
collision-resistance in the standard model, and (2) indifferentiability from
a monolithic random oracle when the mixing stages themselves are indif-
ferentiable from a random oracle that observes injectivity. We instantiate
our new design approach by specifying a blockcipher-based construction
that appropriately realizes the mixing stages.
Joint work with Thomas Shrimpton
References:
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Petros Mol, UCSD
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Wed, October 3, 2007, 11am-12pm, CSE 4109
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Topic: Lattices and Cryptography
Abstract: Historically, the study of lattices has been closely related to
areas such as theory and geometry of numbers. The invention of LLL
algorithm in 1982 and some intractability results for computational
problems related to lattices motivated the use of lattices in
applications such as factorization of integer polynomials, integer
programming and Public-Key Cryptography. Especially in PKC, lattice
theory has played a crucial role in the definition of new cryptosystems,
in the study of cryptographic primitives and in cryptanalysis.
In this talk, we present some of the most representative
applications of lattices in Cryptography with emphasis on cryptanalytic
attacks on RSA Cryptosystem. We present how Coppersmith's technique for
finding small solutions to polynomial equations can be used to attack
certain instances of RSA Cryptosystem. Such attacks include low public
exponent , factoring and low private exponent attacks. We conclude by
presenting a nice deterministic reduction of factoring the RSA modulus
to finding the private key.
References:
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,
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Tuesdays at 2pm, AP&M 7421
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Topic:
Combinatorics Summer Reading Seminar
Abstract: The initial theme is to read and discuss papers from STOC 07.
References:
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Sanjoy Dasgupta, CSE, UCSD
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Thursday June 7, 2007, 11am, CSE 4109
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Topic: Random projection trees and low-dimensional manifolds
Abstract: The curse of dimensionality has traditionally been the bane of nonparametric
statistics (histograms, kernel density estimation, nearest neighbor search,
and so on), as reflected in running times and convergence rates that are
exponentially bad in the dimension. This problem is all the more pressing
as data sets get increasingly high dimensional.
Recently the field has been rejuvenated in several ways, of which perhaps the
most promising is the realization that a lot of real-world data which appears
high-dimensional in fact has low "intrinsic" dimension in the sense of lying
close to a low-dimensional manifold. In the past few years, there has been a
huge interest in learning such manifolds from data, and then using the
learned structure to transform the data into a lower-dimensional space where
standard statistical methods generically work better.
I'll exhibit a way to benefit from intrinsic low dimensionality without
having to go to the trouble of explicitly learning its fine structure.
Specifically, I'll present a simple variant of the ubiquitous k-d tree
(a spatial data structure widely used in machine learning and statistics)
that is provably adaptive to low dimensional structure. We call this a
"random projection tree" (RP tree).
Along the way, I'll discuss different notions of intrinsic dimension --
motivated by manifolds, by local statistics, and by analysis on metric
spaces -- and relate them. I'll then prove that RP trees require resources
that depend only on these dimensions rather than the dimension of the space
in which the data happens to be situated.
This is work with Yoav Freund.
References: http://charlotte.ucsd.edu/~dasgupta/papers/rptree-tr.pdf
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Daniele Micciancio, UCSD
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Thursday May 24, 2007, 11am, EBU3b 4109
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Topic: Tight reductions among lattice approximation problems
Abstract: The most important and widely studied approximation problems
on point lattices are:
- the shortest vector problem (SVP): given a lattice find the
shortest nonzero vector in the lattice.
- the closest vector problem (CVP): given also a target point,
find the lattice point closest to the target.
- the shortest independent vector problem (SIVP): given a lattice
find n linearly independent lattice point that are as short as
possible.
The first two problems have many applications in theoretical computer
science and combinatorial optimization. The last one plays a fundamental
role in the construction of lattice based cryptographic function from
worst-case complexity assumptions.
How do these problems relate to each other? Are they equivalent under
polynomial time reductions? Are some harder than others? In this talk
I will survey the current state of knowledge about the relation among
lattice approximation problems, present some new results, and describe
the remaining open problems. Goldreich et al. have shown that SVP is
not harder than CVP, in the sense that there is a reduction from SVP
to CVP that preserves both the approximation factor, dimension and rank
of the lattice. The main new result presented in this talk is a similar
tight reduction from SIVP to CVP. The reduction yields faster algorithms
to solves SIVP exactly, improving the running time of the best previously
known solution from n!*3^n to n!.
References:
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Shai Halevi, IBM Watson
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Thursday May 17, 2007, 11am, CSE 4109
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Topic: Mitigating Dictionary Attacks on Password-Protected Local Storage
Abstract: We address the issue of encrypting data in local storage using a key
that is derived from the user's password. The typical solution in use
today is to derive the key from the password using a cryptographic
hash function. This solution provides relatively weak protection,
since an attacker that gets hold of the encrypted data can mount an
off-line dictionary attack on the user's password, thereby recovering
the key and decrypting the stored data.
We propose an approach for limiting off-line dictionary attacks in
this setting *without relying on secret storage or secure
hardware*. In our proposal, the process of deriving a key from the
password requires the user to solve a puzzle that is presumed to be
solvable only by humans (e.g, a CAPTCHA). We describe a simple
protocol using this approach: many different puzzles are stored on the
disk, the user's password is used to specify which of them need to be
solved, and the encryption key is derived from the password *and the
solutions of the specified puzzles*.
Completely specifying and analyzing this simple protocol, however,
raises a host of modeling and technical issues, such as new properties
of human-solvable puzzles and some seemingly hard combinatorial
problems. Here we analyze this protocol in some interesting special
cases.
(Joint work with Ran Canetti and Michael Steiner)
References:
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Charanjit Jutla, IBM Watson
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Monday, May 14, 2007, 2:30pm, room CSE 4217
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Topic: SHA and Average Case NP-Hardness
Abstract: We show a problem with uniform distribution to be hard for
flat-NP, where flat-NP is defined to be
distributional NP problems (dist-NP) with distributions smooth w.r.t.
uniform.
We show that this problem models the inversion problem of cryptographic
hash function SHA-1, but with uniform distribution on the output.
On the other hand, we show that basing oneway-ness even on hardness
of flat-NP seems unlikely. To this end, we define new
complexity classes Avg-NP (not to be confused with dist-NP),
and Avg-AM. Extending a result of Akavia et al., we show that for
size-verifiable
functions f, there is no oblivious reduction from flat-NP hard languages to
average case inverting f, unless flat-NP is in Avg-coAM. A similar result
holds for dist-NP. We mention that flat-NP includes the discrete log
problem
over finite fields.
References:
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Sebastian Cioaba, UCSD, Math
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Thursday May 10, 2007, 11am-12am, Room EBU3b (CSE) 4109
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Topic: Separating systems, perfect hash functions and hypergraph cut covers
Abstract: A separating system is a family of disjoint subsets of a set with n
elements that "separates" all the pairs of elements from [n]. A family of
perfect hash functions provides a means for storing k-element subsets of a
set with n elements. In this talk, we will discuss these objects and their
connections to graph and hypergraph covering problems. This is joint work
with Andre Kundgen (Cal State San Marcos).
References:
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Kamalika Chaudhuri, UC Berkeley
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Tuesday May 8, 2007 at 1pm, CSE 4140
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Topic: Clustering using Correlation and Independence
Abstract: Clustering, a method of finding structure in unlabelled data by grouping the data points into few groups based on a similarity measure, has many applications in AI, Physics and Biology. A simple theoretical model that captures clustering is the problem of learning mixtures of distributions. In this setting, one is given sample points generated from a mixture of T distributions of a certain type, and the goal is to recover these distributions and classify the points correctly.^M
In this talk, motivated by an application in biology, we focus on learning mixtures of product distributions. The crux of the problem is learning the centers of the distributions. Singular Value Decomposition (SVD) is extensively used to find the T-dimensional subspace that contains the T centers. While SVD is the basis of provably effective algorithms, it is known to be ineffective in situations where the noise has high variance.^M
We present a simple method which simultaneously exploits the correlation between the signal features and independence between the noise features to effectively separate the centers of the distributions. Our method has performance comparable to SVD based algorithms for learning mixtures of product distributions, and successfully clusters mixtures of axis-aligned Gaussians in certain cases where SVD provably fails.
References:
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Gyula Katona, Renyi Institute (Budapest)
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Thursday May 3, 2007, 11am-12am, Room EBU3b (CSE) 4109
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Topic:
Forbidden inclusion patterns in families of subsets
Abstract: (PDF)
References:
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Andy Drucker, CSE, UCSD
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Thursday April 26, 2007, 11am, in EBU3b 4109
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Topic:
The Complexity of Natural Counting Methods in Combinatorics
Abstract:
- There are n! distinct n x n 0/1 permutation matrices.
- Half of all binary strings of a given length have an odd number of ones.
What do the proofs of these familiar counting facts reveal about the
structural complexity of the associated sets?
In this presentation on work in progress, I will describe how circuit and
automata classes can be given to model the power of natural counting methods
based on combinatorial operations such as disjoint union and cartesian
product. I will also describe how to prove exponential lower bounds for
one such class, showing, for example, that constructively counting the
permutation matrices requires an inherently richer vocabulary than does
counting the odd-weight strings.
References:
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Vadim Lyubashevsky, CSE, UCSD
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Thursday April 19, 2007, 11am, Room EBU3b 4109
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Topic: Cryptographic Hardness for Learning Intersections of Halfspaces
Abstract: We give the first representation-independent hardness results for PAC learning intersections of halfspaces, a central concept class in computational learning theory. Our hardness results are derived from two public-key cryptosystems due to Regev, which are based on the worst-case hardness of well-studied lattice problems. Specifically, we prove that a polynomial-time algorithm for PAC learning intersections of $n^{epsilon}$ halfspaces (for a constant $epsilon>0$) in $n$ dimensions would yield a polynomial-time solution to $tilde O(n^{1.5})$-unique shortest vector problem. We also prove that PAC learning intersections of $n^{epsilon}$ low-weight halfspaces would yield a polynomial-time quantum solution to $tilde O(n^{1.5})$-shortest vector problem and $tilde O(n^{1.5})$-shortest independent vector problem. By making stronger assumptions about the hardness of these lattice problems, we show that there is no polynomial-time algorithm for learning intersections of $log^c n$ halfspaces in $n$ dimensions, for $c>0$ sufficiently large. Our approach also yields the first representation-independent hardness results for learning polynomial-size depth-$2$ neural networks and polynomial-size depth-$3$ arithmetic circuits.
(based on a FOCS 2006 paper by Adam Klivans and Alex Sherstov)
References: http://eccc.hpi-web.de/eccc-reports/2006/TR06-057/index.html
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Atri Rudra, University of Washington
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Monday April 16, 2007, 11:00am, EBU 3B CSE 1202
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Topic: Error-correction with Information-theoretically Optimal Data Rate
Abstract: Suppose you want to communicate k packets over a noisy communication
channel. This is a common scenario when transmitting data over any real
world channel such as the Internet or the telephone line. In order to
tolerate errors, you transmit a redundant collection of n=c*k packets.
When can you communicate reliably despite the adverse effects of the noisy
channel? That is, when can the receiver recover the original message even
in the presence of corrupted packets?
Clearly, the receiver must receive at least k correct packets to have any
hope of recovering the original message. In this talk, I will describe an
efficient encoding (and decoding) scheme that achieves this information
theoretical limit: for any eps>0, the receiver can recover the original
message as long as (1+eps)*k packets are not corrupted. The location of
the correct packets and the errors can be chosen adversarially by the
channel.
This scheme achieves the optimal trade-off (called "capacity") between
redundancy and error-resilience for a malicious noise model in which the
channel can corrupt the transmitted symbols arbitrarily subject to a bound
on the total number of errors. These results are obtained in an
error-recovery model called list decoding. In this talk I will introduce
and motivate list decoding and then give an overview of our encoding
scheme.
I will also briefly discuss my other work in game theory, sublinear
algorithms, approximation algorithms and coding theory. In particular, I
will talk about my results in profit maximizing auctions, lower bounds for
data stream algorithms and rank aggregation.
References:
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Sergey Yekhanin, MIT
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Thursday April 12, 4pm, 2007, AP&M Room #6402
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Topic: New Locally Decodable Codes and Private Information Retrieval Schemes
Abstract: A q-query Locally Decodable Code (LDC) is an error-correcting code
that encodes an n-bit message x as a codeword C(x), such that one can
probabilistically recover any bit x_i of the message by querying only q bits
of the codeword C(x), even after some constant fraction of codeword bits has
been corrupted. The goal of LDC related research is to minimize the length
of such codes.
A q-server private information retrieval (PIR) scheme is a cryptographic
protocol that allows a user to retrieve the i-th bit of an n-bit string x
replicated between q servers while each server individually learns no
information about i. The goal of PIR related research is to minimize the
communication complexity of such schemes.
We present a novel algebraic approach to LDCs and PIRs and obtain vast
improvements upon the earlier work. Specifically, given any Mersenne prime
p=2^t - 1, we design three query LDCs of length Exp(n^{1/t}), for every
n. Based
on the largest known Mersenne prime, this translates to a length of less
than Exp(n^{10^{-7}}), compared to Exp(n^{1/2}) in the previous
constructions.
We also design 3-server PIR schemes with communication complexity of
O(n^{10^{-7}}) to access an n-bit database, compared to the previous best
scheme with complexity O(n^{1/5.25}).
It has often been conjectured that there are infinitely many Mersenne
primes. Under this conjecture, our constructions yield three query locally
decodable codes of subexponential length and three server private
information
retrieval schemes with subpolynomial communication complexity.
References:
http://theory.lcs.mit.edu/~yekhanin/Papers/nice_PIR.pdf
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Martin Grohe, Humboldt-Universitaat zu Berlin
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Thursday April 12, 11am-12pm, 2007, Room EBU3b (CSE) 4109
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Topic: An Isomorphism Between Exponential and Parameterized Complexity Theory
Abstract: Exponential complexity theory is concerned with the exact
complexity of hard algorithmic problems, and in particular with the
question of whether such problems are solvable in subexponential time.
For example, a central question in this area is whether 3-SAT is
solvable in time 2^o(n), where n denotes the number of variables.
Parameterized complexity theory is also concerned with exact algorithms
for hard algorithmic problems; here the question is whether the
exponential running time that may be required to solve a problem can be
confined to be exponential in some parameter of the problem instances,
such as the degree of a graph, that can be expected to be small for the
"relevant" instances.
We show that exponential and parameterized complexity theory are
isomorphic in a precise sense: The so-called "miniaturization mapping",
introduced by Fellows and others, is one-to-one and onto (in the
relevant range of problems), and it preserves the partial order induced
by the standard reductions on both sides. Moreover, we show that the
mapping acts quite naturally on important problems and complexity classes.
(This is joint work with Yijia Chen.)
References:
http://www2.informatik.hu-berlin.de/~grohe/pub/chegro07+.pdf
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Julia Chuzhoy, IAS
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Friday, April 6th 2007 at 11:00am, CSE1202
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Topic: Cuts and Flows in Directed Graphs
Abstract: Cuts and flows are among the most basic graph theoretic notions.
Applications that require solving graph cut or flow problems arise
in almost every area of computer science. The study of the
connection between flows and cuts dates back to the late fifties
when Ford and Fulkerson proved that in the single-commodity
environment, minimum cut equals maximum flow in any graph. A natural
generalization of this result would be establishing the relationship
between flows and cuts in the presence of multiple commodities. This
relationship is usually expressed via the notion of flow-cut gap:
the maximum ratio, achievable for any graph, between the maximum
multi-commodity flow and the corresponding cut value, called minimum
multicut.
Flow-cut gaps have been extensively studied for more than five
decades now, and they are widely used in the design and the analysis
of algorithms. One of the major breakthroughs in this area is a
complete understanding of the flow-cut gap in undirected graphs,
which was proved to be logarithmic. In spite of this success, the
flow-cut gaps have remained poorly understood in directed graphs. In
particular, it has remained an open question whether the flow-cut
gap in directed graphs is also logarithmic. In this talk we will
answer this question in the negative by showing that, in sharp
contrast to the undirected case, the flow-cut gap in directed graphs
is polynomial.
References:
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Konstantin Pervyshev, CSE, UCSD
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3 PM Wed. March 21, 2007, CSE 4109
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Topic: Proofs of Work & Memory-Bound Functions
Abstract: In 1992, Dwork and Naor proposed that e-mail messages be accompanied by
easy-to-check proofs of computational effort in order to discourage spam.
They proposed specific CPU-bound functions for this purpose. Burrows
suggested that, since memory access speeds vary across machines much less
than do CPU speeds, memory-bound functions may behave more equitably than
CPU-bound functions.
In this talk, we will provide a construction of proofs-of-work based on a
memory-bound function and prove an asymptotically tight amortized lower
bound on the number of memory accesses required to compute an acceptable
proof of effort.
(based on a CRYPTO 2003 paper by C. Dwork, A. Goldberg and M. Naor)
References: http://www.wisdom.weizmann.ac.il/~naor/PAPERS/mem_abs.html
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Milena Mihail, Georgia Tech
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Wed March 21, 2007 at 11am, CSE (EBU3B) 1202
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Topic: Network Performance and Spectral Metrics
Abstract: What parameters of massive networks,
such as the Internet, the Web, and peer-to-peer networks,
are critical to protocol performance?
Can we measure and control these parameters
and hence improve network performance?
Can we predict how performance will scale
with the size of these networks?
In this talk I will argue that a critical parameter is
the expansion, or conductance of the graph underlying
the network topology. This is also closely related to the
spectral gap of a suitable normalization of the adjacency
matrix of this graph. I will present both experimental
studies of these parameters using real network data, and
theoretical studies using models such as power-law graphs.
I will further present efficient distributed algorithms
that maintain network topologies with good expansion,
conductance and spectral gap.
References:
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Olgica Milenkovic, University of Colorado, Boulder
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Wed, March 14, 2007, 3 PM, 4109 EBU3b
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Topic: Average case analysis of Gosper's algorithm for indefinite summation of hypergeometric terms.
Abstract: When addressing questions arising in combinatorial theory, one frequently
encounters the problem of evaluating sums of functions of binomial terms.
Sometimes, these, and certain more general sums of hypergeometric terms,
including binomial coefficients, factorials, power and rational functions,
have surprisingly simple "closed-form" expressions. Interestingly, there
exist completely automatic procedures for determining if such expressions
can be found and of what form they are. The key component of all such
procedures is Gosper's algorithm.
In this talk, we present an asymptotic analysis of the average-case
complexity of Gosper's algorithm, based on a novel class of probabilistic
transforms for urn-model occupancies, Tauberian theorems and generalized
random walk statistics. The results developed in the course of this
analysis are of independent interest in other areas of theoretical
computer science, probability and coding theory.
This is a joint work with Kevin Compton from the University of Michigan,
Ann Arbor.
References: http://ece-www.colorado.edu/~milenkov/gosper2.ps
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Vijay Vazirani,
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Monday, March 12, 2007, 11:00 AM in CSE 1202
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Topic: Markets and the Primal-Dual Schema
Abstract: The Internet has seen the emergence of several novel, computationally
intensive markets, including Google's AdWords market, eBay's auctions
market, and Yahoo! and Amazon's online markets which depend heavily
on recommender systems. This is just the beginning of a much larger
revolution in which algorithmic considerations are bound to have an
impact (indeed, Internet companies are gearing up to this fact through
massive research investments).
The study of markets, within general equilibrium theory, occupied a
central place in mathematical economics for over a century. In this
talk, I will describe recent results on efficiently computing
equilibria for traditional as well as new market models. This body
of work provides a nice starting point for building an algorithmic
theory of markets which can address today's needs. Interestingly
enough, in these early works, the classical algorithm design technique
of primal-dual schema plays a central role.
References:
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David Kempe, USC
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Wed. Mar. 6, 2007, 3-4pm, EBU3b 4109
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Topic: On the Bias of Traceroute Sampling, or: Power-law Degree Distributions in Regular Graphs.
Abstract: Understanding the structure of the Internet graph is a crucial step
for building accurate network models and designing efficient
algorithms for Internet applications. Yet, obtaining its graph
structure is a surprisingly difficult task, as edges cannot be
explicitly queried. Instead, empirical studies rely on traceroutes to
build what are essentially single-source, all-destinations,
shortest-path trees. These trees only sample a fraction of the
network's edges, and a recent paper by Lakhina et al. found
empirically that the resuting sample is intrinsically biased. For
instance, the observed degree distribution under traceroute sampling
exhibits a power law even when the underlying degree distribution is
Poisson.
In this talk, we study the bias of traceroute sampling systematically,
and, for a very general class of underlying degree distributions,
calculate the likely observed distributions explicitly. To do this, we
use a continuous-time realization of the process of exposing the BFS
tree of a random graph with a given degree distribution, calculate the
expected degree distribution of the tree, and show that it is sharply
concentrated. As example applications of our machinery, we show how
traceroute sampling finds power-law degree distributions in both
d-regular and Poisson-distributed random graphs.
Thus, our work puts the observations of Lakhina et al. on a rigorous
footing,
and extends them to nearly arbitrary degree distributions.
(Joint work with Dimitris Achlioptas, Aaron Clauset, and Cristopher Moore.)
References: http://www-rcf.usc.edu/~dkempe/publications/bfs.pdf
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Mohan Paturi, CSE, UCSD
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Wed. Feb. 14 and 21, 2007, 3-4pm, EBU3b 4109
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Topic: Expander Graphs
Abstract: I will provide part I of a two part talk
which culminates in zig-zag product construction of expander graphs.
Today, we will cover preliminary ideas and prove a theorem
that connect expansion with eigenvalues.
References:
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Russell Impagliazzo, CSE, UCSD
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Wed. Feb. 7, 2007, 3-4pm, EBU3b 4109
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Topic: A Chernoff style direct product theorem
Abstract: Consider a challenge-response protocol, where a legitimate
user should have probability at least $\alpha$ of responding
correctly, whereas an attacker has probability at most
$\beta < \alpha$ of responding correctly. One example is a CAPTCHA
challenge, where a human should have a significantly higher chance
of answering a single challenge (e.g., uncovering a distorted
letter) than an attacker. Another example would be a zero-knowledge
argument system without perfect completeness.
A natural approach to boost the gap between legitimate users
and attackers would be to issue many challenges, and accept if
the response is correct for more than a threshold fraction,
where the threshold is chosen between $\alpha$ and $\beta$.
We give the first proof that parallel repetition with thresholds
improves the security of such protocols. We do this with a
very general result about an attackers ability to solve a large
fraction of many independent instances of a hard problem, showing
a Chernoff-like convergence of the fraction solved correctly to
the probability of failure for a single instance.
This is a joint work with Ragesh Jaiswal(UCSD) and Valentine Kabanets (SFU).
References:
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Andrew Drucker, CSE, UCSD
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Wed. Jan 31, 2007, 3-4pm, EBU3b 4109
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Topic: Property Testing
Abstract: Property testing is a recently developed algorithmic
paradigm inspired by the need for fast (even
constant-time!) approximate solutions to problems with
very large data sets. I will introduce the field,
give representative examples of testing algorithms and
their analysis, and describe lower bounds for the model.
References:
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Manindra Agrawal, IIT Kanpur
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Mon. Jan. 22, 2007, 11-12, 1202 EBU3b
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Topic: Determinant Versus Permanent
Abstract: I will talk about the problem of expressing permanent of matrices as determinant of
(possibly larger) matrices. This problem has close connections with complexity
of arithmetic computations: complexities of computing permanent and determinant
roughly correspond to arithmetic versions of the classes NP and DP respectively.
I will survey known results about their relative complexity and describe two recently
developed approaches that might lead to a proof of the conjecture that permanent
can only be expressed as determinant of superpolynomial-sized matrices.
References: www.cse.iitk.ac.in/users/manindra/survey/Determinant.pdf
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Bakhadyr Khoussainov , University of Auckland
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Wed. 6 Jan, 2007, 3pm, Ebu3b 4109
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Topic: Automatic Structures
Abstract: We introduce the concept of automatic structure. Informally, these
are structures that can be defined in terms of automata. By automata
we mean any of the following machines: finite automata, tree automata,
Buchi automata, and Rabin automata.
Nerode and the speaker initiated the systematic study of automatic
structures in 94. An important property of automatic structures is
that these structures are closed under the first order interpretations
and have effective semantics. In particular, the first order theory
of any automatic structure is decidable.
The theory of automatic structures has become an active research
area in the last decade with new and exciting results. In this talk
we survey recent results in the area and outline some of the interesting
proofs. The talk will provide many examples.
Some of the results of the talk are published in LICS 01-04 and
STACS04 conference proceedings. Results are joint with Nerode,
Rubin, Stephan, and Nies.
References:
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Evdokia Nikolova, MIT
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Wed. 12 Dec, 3pm, Ebu3b 4109
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Topic: Stochastic Shortest Paths via Quasi-Convex Maximization
Abstract: We consider the problem of finding shortest paths in a graph with
independent randomly distributed edge lengths. Our goal is to
maximize the probability that the path length does not exceed
a given threshold value (deadline).
We give a surprising exact $n^{\Theta(\log n)}$
algorithm for the case of normally distributed edge lengths,
which is based on quasi-convex maximization.
We then prove average and smoothed polynomial bounds for this
algorithm,
which also translate to average and smoothed bounds for the
parametric shortest path problem, and extend to a more general
non-convex optimization setting.
We also consider a number other edge length distributions, giving
a range of exact and approximation schemes.
joint work with Matthew Brand, Jonathan Kelner, Michael Mitzenmacher
References:
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Andrew McGregor,
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Wed. 6 Dec, 3pm, Ebu3b 4109
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Topic: Estimating the Entropy of a Data Stream
Abstract: In this talk we will present a list of m values from a universe [n].
The list may only be read from left to right and you only have polylog
(n,m) bits of memory. What can you compute about the underlying
distribution of the values in the stream? In particular, can you
approximate the entropy of this distribution?
The above constraints characterize the data stream model, a model
that abstracts some of the challenges faced when processing network
traffic, database records, and data from external memory devices.
Over the last ten years numerous theoretical results have been proven
for this model including the Goedel prize winning work of Alon,
Matias, and Szegedy on estimating frequency moments.
In addition to presenting a long list of values, this talk will
feature the results of joint work with Amit Chakrabarti (Dartmouth
College) and Graham Cormode (AT&T Labs). This includes a near-optimal
algorithm and lower-bound for estimating Shannon entropy and
consideration of higher-order entropy and the entropy of a random walk.
Bonus!
Time permitting we'll also discuss some new results on approximating
information theoretic distances such as Kullback-Leibler and Jensen-
Shannon in the data stream model. This is joint work with Sudipto
Guha (University of Pennyslvania) and Piotr Indyk (MIT).
References: http://talk.ucsd.edu/andrewm/papers/07-soda1.pdf
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Du Peng,
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29 Nov, Wed. at 3 PM, in CSE 4109
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Topic: Bipartite graph matching for points on a circle
Abstract: Finding a minimum-cost matching in balanced bipartite graph whose nodes
are on a circle is an interesting problem, which has been intensively
studied by many researchers. One basic assumption is the defined cost
function has to obey quadrangle inequality. We hereby present linear
algorithms for two variations of this matching problem, each of which is
dealing with a different cost function. In the first problem, the cost
function is given by the shortest arc length between any two nodes of
different color. Observation that there exists a greedy solution where
every node matches to its neighbor after certain classification leads a
linear algorithm to this simple case. For the second, the cost function is
provided by Euclidean distance between two nodes. The cumulative property
of the first cost function doesn’t hold any more which makes the greedy
solution incorrect. We introduce another linear algorithm developed by
Samuel R. Buss and Peter N. Yianilos for this case by the insight into the
properties of the constrained optimal solution. Finally, both algorithms
are generalized for other types of cost functions and for the nodes that
lie on shapes other than circles.
References:
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Russell Impagliazzo, CSE, UCSD
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Wed. 15 November 2006, 3pm, CSE 4109
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Topic: A unified approach to tail inequalities
Abstract: A tail inequality
is a bound on the probability that a random
variable is far from its expectation. Some
tail inequalities that are widely used include
Chebyshev bounds, Chernoff bounds, and the
Martingale bound (Azuma's inequality). This
talk will show that these bounds are related,
by giving a notion of tail-bound preserving
reduction between families of random variables.
The emphasis will be on simplifying and unifying
the proofs of versions of the inequalities, often
at the expense of getting weaker bounds.
References:
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Danny Harnik, Technion, Israel
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Friday, Nov 10, 2006, 3 PM, Ebu3b CSE 4109
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Topic: On the Power of the Randomized Iterate
Abstract: We consider two of the most fundamental theorems in Cryptography. The
first, due to Haastad, Impagliazzo, Levin and Luby (known as HILL), is
that pseudorandom generators can be constructed from any one-way
function. The second, due to Yao in 1982, states that the existence of
weak one-way functions implies the existence of full fledged one-way
functions. The above reductions, however, are not as security
preserving as one may desire. The main reason for the security
deterioration is the input blow up in both of these constructions.
This work revisits a technique that we call the Randomized Iterate,
introduced by Goldreich, Krawczyk and Luby. The technique was used to
give a construction of pseudorandom generators from regular one-way
functions. We simplify and strengthen this technique in order to
obtain a similar
reduction where the seed length of the resulting generators is as
short as O(n log n) rather than \Omega(n^3) in the original proposed
generator. We give a reduction with similar parameters for security
amplification of regular one-way functions.
We also show that the randomized iterate may even be useful in the
context of an arbitrary one-way function. In particular, we use the
randomized iterate to replace the basic building block of the HILL
construction. This modification improves the efficiency by an O(n^3)
factor and reduces the seed length by a factor of n (which also
implies improvement in the security of the construction).
Joint work with Iftach Haitner and Omer Reingold.
References:http://www.cs.technion.ac.il/~harnik/Randomized_Iterate.pdf
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Konstantin Pervyshev, CSE, UCSD
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1st Nov, 2006, 3pm, CSE EBU3b 4109
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Topic: Time Hierarchies for Heuristic Algorithms
Abstract: Although a time hierarchy for deterministic algorithms was one of the first results in complexity theory, it is still unclear whether a time hierarchy exists for probabilistic algorithms. Recently, Fortnow and Santhanam (FOCS'04) proposed to consider average-case setting and proved the existence of a time hierarchy for heuristic algorithms in BPP, one of probabilistic classes. We develop an alternative approach and give a simpler proof of this result. Further, we show that time hierarchies exist for heuristic algorithms in some other classes, such as NP, AM and MA.
References: http://eccc.hpi-web.de/eccc-reports/2006/TR06-131/index.html
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Max Alekseyev, CSE, UCSD
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Wed. 25 October 2006, 3pm, CSE 4109
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Topic: Multi-Break Rearrangements and Fragile Regions in Human Genome
Abstract: Multi-break rearrangements break a genome into multiple fragments
and further glue them together in a new order. While multi-break
rearrangements were studied in depth for k=2 breaks, the
k-break rearrangement distance problem for an arbitrary k remains
unsolved. We prove a duality theorem for multi-break rearrangement
distance and give a polynomial algorithm for computing this
distance. Using these results, we analyze the recent controversy
about the Fragile Breakage Model of chromosome evolution.
References:
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Reid Andersen, MATH, UCSD
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18 Oct, 2006, 3pm, CSE EBU3b 4109
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Topic: Local Partitioning using PageRank
Abstract: A local graph partitioning algorithm finds a cut near a specified
starting vertex, and runs in time proportional to the small side of
the cut, rather than the size of the input graph. In this talk,
we present a local partitioning algorithm which finds a cut by
computing a PageRank vector with a specified starting distribution.
By combining small cuts found by this algorithm, we obtain a cut
with conductance Phi and approximately optimal balance in time
O(m log^4 m / Phi^2), where m is the number of edges in the graph.
This is joint work with Fan Chung and Kevin Lang.
References: http://www.math.ucsd.edu/~fan/wp/localpartition.pdf
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Benny Sudakov, Princeton University
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Wed. October 11, 2006, 3 PM, in 4109 CSE (EBU3b)
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Topic: Additive Approximation for Edge-Deletion Problems
Abstract: A graph property is monotone if it is closed under removal of vertices and edges. In this talk we consider the following edge-deletion problem; given a monotone property P and a graph G, compute the smallest number of edge deletions that are needed in order to turn G into a graph satisfying P. We denote this quantity by $E_P(G)$. Our first result states that for any monotone graph property P, any $\epsilon >0$ and n-vertex input graph $G$ one can approximate $E_P(G)$ up to an additive error of $\epsilon n2$
Our second main result shows that such approximation is essentially best possible and for most properties, it is NP-hard to approximate $E_P(G)$ up to an additive error of $n^{2-\delta}$, for any fixed positive $\delta$.
The proof requires several new combinatorial ideas and involves tools from Extremal Graph Theory together with spectral techniques. Interestingly, prior to this work it was not even known that computing $E_P(G)$ precisely for dense monotone properties is $NP$-hard. We thus answer (in a strong form) a question of Yannakakis raised in 1981.
Joint work with N. Alon and A. Shapira.
References: http://www.math.princeton.edu/~bsudakov/edit-distance.pdf
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Nina Balcan, CMU
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Thursday Oct 5, 2pm-3pm, EBU3b 4140
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Topic: Mechanism Design, Machine Learning and Pricing Problems
Abstract: In this work, we make an explicit connection between machine learning and mechanism design. In doing so, we obtain a unified approach for
considering a variety of profit maximizing mechanism design problems, including many that have been previously considered in the literature. In particular, we use techniques from sample complexity in machine learning theory to reduce problems of incentive compatible mechanism design to standard algorithmic questions. We apply these results to a wide variety of revenue-maximizing pricing problems, including the problem of
auctioning a digital good, the attribute auction problem, and the problem of item pricing in unlimited supply combinatorial auctions.
It is worth noting that from a learning perspective, these settings present several unique challenges: the loss function is discontinuous and
asymmetric, and the range of bidders' valuations may be large.
This is joint work with Avrim Blum, Jason Hartline, and Yishay Mansour.
References:
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Saurabh Panjwani, CSE, UCSD
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4th October, 2006, 3pm, EBU3b 4109
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Topic: Soundness of Symbolic Encryption in the presence of Adaptive Corruptions
Abstract: Proving the security of cryptographic protocols in the presence of attackers who can corrupt protocol participants during the execution of the protocol, in an "adaptive" manner, can be quite a challenging task. It is known that, in general,
non-adaptive security of a protocol (security against non-adaptively corrupting adversaries) does not imply security against adaptive corruptions (that is, there exist protocols that are provably secure against non-adaptive corruptions but which can be completely broken by adaptive adversaries). The situation is particularly grim for protocols that use encryption as the fundamental primitive; even the strongest notions of encryption security are not known to imply adaptive security of protocols constructed using such encryption schemes. In
fact, it is commonly believed that in order to be able to prove an encryption protocol adaptively secure, one is required to use non-standard encryption schemes(that is, encryption schemes that satisfy security criteria stronger than the standard ones like semantic security against chosen plaintext attacks).
In this work, we show that under some reasonable restrictions on the protocol syntax, it is possible to argue about the adaptive security of encryption protocols, in a manner that does NOT require using non-standard definitions of encryption security. We present a general computational soundness theorem, which establishes
that in any symmetric-key based encryption protocol, if the underlying encryption scheme is semantically secure, and if encryption "cycles" are absent, then security against adaptive corruptions is achievable via a reduction factor of O((2n)^{2l}), with n and l being the "size" and the "depth" of the key graph generated
during any protocol execution. Since, in most protocols of practical interest, the depth of key
graphs (measured as the longest sequence of ciphertexts of the form Encrypt_{k_1}(k_2),
Encrypt_{k_2}(k_3), Encrypt_{k_3}(k_4), ... ever generated), is much smaller than their size,
this gives us a powerful tool to prove adaptive security of such protocols, and with very
reasonable assurances on the strength of the protocol against adaptive attacks.
If time permits, we will also present an application of the soundness theorem. Specifically, we will show how the soundness theorem can be used to prove a variant of the
Logical Key Hierarchy (LKH) protocol adaptively secure. LKH is a rather simple protocol that
has attracted considerable interest in the cryptography community but whose adaptive
security has hitherto remained unresolved.
References: Draft
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Sashka Davis, CSE, UCSD
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Wednesday 27th Sept., 3pm, EBU3b 4109
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Topic: Online Algorithms to Minimize Resource Reallocations and Network Communication
Abstract: In this paper, we consider two new online optimization problems (each with several variants), present similar online algorithms for both, and show that one reduces to the other. Both problems involve a control trying to minimize the number of changes that need to be made in maintaining a state that satisfies each of many users' requirements. Our algorithms have the property that the control only needs to be informed of a change in users needs when the current state no longer satisfies the user. This is particularly important when the application is one of trying to minimize communication between the users and the control.
References: www-cse.ucsd.edu/~sdavis/sensor.pdf
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Russell Impagliazzo, CSE, UCSD
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May 31, 2006, 12:30, EBU3b 4109
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Topic: On the Complexity of Succinct Zero-Sum Games
Abstract:
References: L. Fortnow, R. Impagliazzo, V. Kabanets, C. Umans
"On the Complexity of Succinct Zero-Sum Games".
IEEE Conference on Computational Complexity 2005: 323-332
[http://dx.doi.org/10.1109/CCC.2005.18]
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Yoav Freund, CSE, UCSD
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Wed May 24, 2006, 12:30pm, EBU3b 4109
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Topic: Drifting games in continuous time
Abstract: The computational task that lies in the core of many machine learning problems is the minimization of a cost function called the training error. This problem is frequently solved by local search algorithms such as gradient descent. On the other hand, the cost function can usually be expressed as a sum over many terms, each corresponding to
the loss of the model on a single training example. We show that the iteratively minimizing a cost function of this form by local search
is closely related to the following game:
Imagine you are a shepherd in charge of a large herd of sheep and your goal is to concentrate the sheep in a particular small area by nightfall. Your influence on the sheep movements is represented by vectors which define the direction in which you want each sheep to move. The lengths of the vectors correspond to the fraction of your
"energy" that you spend on moving the particular sheep, and these lengths sum to one. The sheep then have to respond by moving in a way that has a slight correlation with the influence direction on average.
We characterize the min/max solution to this game and show that by taking the appropriate small-step/continuous-time limit, this solution
can be characterized by a stochastic differential equation.
By solving this differential equation we re-derive some known boosting and on-line learning algorithms as well as design some new ones with
desirable properties.
This is Joint work with Manfred Opper.
References:
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Vijay Vazirani, Georgia Tech
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May 17, at 11 AM, EBU 3B 1202
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Topic: New Market Models and Algorithms
Abstract: The notion of a ``market'' has undergone a paradigm shift with the Internet -- totally new and highly successful markets have been defined and launched by companies such as Google, Yahoo!, Amazon, MSN and Ebay. Another major change is the
availability of massive computational power for running these markets in a centralized or distributed manner.
In view of these new realities, the study of market equilibria, an important, though essentially non-algorithmic, theory within
Mathematical Economics, needs to be revived and rejuvenated with new models, ideas, and an inherently algorithmic approach.
In this talk, I will give a feel for the exciting work going on on this front and present new results on resource allocation markets. Interestingly enough, this work has also contributed handsomely to the theory of algorithms itself. In particular, the highly successful primal-dual schema from exact and approximation algorithms, which was so far used for combinatorially solving special classes of linear programs, has been extended to solving nonlinear convex programs.
(The talk is self-contained and is meant for a general audience.)
References: http://www-static.cc.gatech.edu/fac/Vijay.Vazirani/EG.pdf
http://eccc.hpi-web.de/eccc-reports/2006/TR06-029/index.html
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Antonio Nicolosi, NYU
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Wednesday May 17th, 1pm, EBU3b 4019
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Topic: Non-Interactive Zero-Knowledge from Homomorphic Encryption
Abstract: We propose a method for compiling a class of Sigma-protocols (3-move public-coin protocols) into non-interactive zero-knowledge arguments. The method is based on homomorphic encryption^M
and _does not_ use random oracles. It only requires that a private/public key pair is set up for the verifier. The method applies to all known discrete-log-based Sigma-protocols.^M
^M
As applications, we obtain non-interactive threshold RSA without random oracles, and non-interactive zero-knowledge for NP more^M
efficiently than by previous methods.^M
^M
Joint work with Ivan Damgaard (Aarhus Univ.) and Nelly Fazio (NYU).^M
References:
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Russell Impagliazzo, CSE, UCSD
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Wednesday 10 May , 12:30, EBU3b 4109
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Topic: Can Every Randomized Algorithm Be Derandomized?
Abstract: Among the most important modern algorithmic techniques is the use of random decisions. Starting in the 1970's, many of the most significant results were randomized algorithms solving basic compuatational problems that had (to that time) resisted efficient deterministic computation [Ber72, SS79, Rab80,
Sch80, Zip79, AKLLR]. In contrast, many of the most exciting recent work has been on derandomizing these same algorithms, coming up with efficient deterministic versions, e.g., [AKS02,Rein05]. This raises the question, can such results be obtained for all randomized
algorithms? Will the remaining classical randomized algorithms be derandomized by similar techniques?
Clear but complicated answers to these questions have emerged from complexity-theoretic studies of randomized complexity classes (e.g., RP and
BPP) and pseudo-random generators. These questions are inextricably linked
to another basic problem in complexity: which functions require large circuits to compute? In this talk, we'll survey some results from the
theory of derandomization. I'll stress connections to other questions, especially circuit complexity, explicit extractors, hardness amplification, and error-correcting codes. Much of the talk is based on joint work with
Valentine Kabanets and Avi Wigderson, but it will also include results by many other researchers.
References:
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wednesdays, 12:00 - 1:30, EBU3b 4109
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Topic: Game Theory in Computer Science
Abstract: STAR for Spring-2006
References:
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Russell Impagliazzo, CSE, UCSD
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8 Dec, 1:00 pm, EBU3B 4217
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Topic: Computational Complexity Since 1980
Abstract: This talk will address trends in the computational complexity theory since 1980. The defining problems and issues for the field were established in the 1960's and 1970's. While many of these problems remain open, what is notable in the subsequent work is the intertwining of these fundamental questions, both through direct implications relating them and through a common toolbox of techniques that can be used to address a variety of seemingly disparate issues in complexity.
We'll show how this unified set of techniques has been used to address and relate a variety of the basic questions in complexity, such as:
1. Hardness of approximation:
To what extent can $NP$-hardness results be circumvented? More precisely, which optimization problems can be efficiently solved approximately?
2. Average-case complexity:
Does $NP$-hardness mean that intractible instances of a problem actually arise? Or can we devise heuristics that solve typical instances? Which problems can be solved on "most" instances?
3. Foundations of cryptography:
Can computational complexity be used as a foundation for cryptography? What kind of computational hardness is needed for such a cryptography?
4. The Power of randomness:
What is the power of randomized algorithms? Should randomized algorithms
replace deterministic ones to capture the intuitive notion of efficient computation?
5. Circuit complexity:
Which problems require many basic operations to compute in non-uniform models such as Boolean or arithmetic circuits? How does the circuit complexity of problems relate to their complexity in uniform models?
6. Constructive combinatorics:
Many mathematically interesting objects, such as from extremal graph theory, are proved to exist non-constructively, e.g., through the
probabilistic method. When can these proofs be made constructive, exhibiting explicit and easily computable graphs or other structures with the desired properties?
References:
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Saurabh Panjwani, CSE, UCSD
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29th Nov, 1:30 pm, EBU3B 4217
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Topic: Append-Only Signatures
Abstract: We present a new cryptographic primitive - Append-only Signatures (AOS) - with the property that any party given an AOS signature Sig[M] on message M can compute Sig[M || M'] for any message M' (where M || M' denotes the concatenation of M and M') while no malicious party can forge a signature on M unless and until a prefix of M has already been signed. Such signatures can be used for implementing credential systems in which one party delegates some information to another while also giving the latter the capability to ``append'' to the existing information, but to do nothing else.
We present several concrete schemes for AOS in the standard model (no random oracles), and prove their security under general complexity-theoretic assumptions. In addition, we find that despite its simple definition, AOS is equivalent to Hierarchical Identity-based Signatures (HIBS) through poly-time reductions. Our investigations indicate that AOS is both useful in practical applications and worthy of further study as a cryptographic primitive.
References: This is the joint work of Eike Kiltz, Anton Mityagin, Saurabh Panjwani and Barath Raghavan and it appeared in ICALP 2005
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Alan Nash, CSE, UCSD
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16 Nov, 1:00pm, EBU3B 4109
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Topic: Testing Logical
Implication in the Finite and Applications to Information Integration
Abstract:
References:
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Santosh Vempala, MIT
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10 Oct, 11:00-12:00, EBU3B 1202
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Topic: Spectral Algorithms and Representations
Abstract: The spectrum of a matrix (or a graph) captures many interesting properties
in surprising ways. Spectral methods (based on eigenvalues and eigenvectors)
are already used for unsupervised learning, image segmentation, to improve
precision and recall in databases and broadly for information retrieval.
The common component of these methods is a projection to the space of a few
singular vectors of the data. In this talk, we describe this idea and focus
on the vital role it plays in efficient algorithms for (a) clustering
object-feature (document-term) matrices and (b) the classical problem of
learning a mixture of Gaussians. We also highlight a property that makes
these methods particularly attractive for large data sets: any matrix (of
any size) contains a "constant-size" submatrix from which an approximate
spectral representation can be efficiently computed.
References:
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Yevgeniy Dodis, NYU
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27th Sept, 4-5:30pm, EBU3B 4217
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Topic: On Extractors, Error-Correction and Hiding All Partial Information
Abstract: Randomness extractors allow one to obtain nearly perfect randomness
from highly imperfect sources randomness, which are only known to contain
"scattered" entropy. Not surprisingly, such extractors have found numerous
applications in many areas of computer science including cryptography. Aside
from extracting randomness, a less known usage of extractors comes from the
fact that they hide all deterministic functions of their (high-entropy) input:
in other words, extractors provide certain level of privacy for the imperfect
source that they use. In the latter kind of applications, one typically needs
extra properties of extractors, such as invertibility, collision-resistance or
error-correction.
In this abstract we survey some of such usages of extractors,
concentrating on several recent results by the speaker. The primitives
we will survey include several flavors of randomness extractors,
entropically secure encryption and perfect one-way hash functions. The
main technical tools will include several variants of the leftover
hash lemma, error correcting codes, and the connection between
randomness extraction and hiding all partial information.
References: http://theory.lcs.mit.edu/~yevgen/ps/ent-survey.ps
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Eike Kiltz , CSE, UCSD
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2 June, 11-12:20, AP&M 5218
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Topic: Threshold Circuit Lower Bounds on Cryptographic Functions
Abstract: In this work, we are interested in non-trivial upper bounds on the
spectral norm of binary matrices M from {-1,1}^NxN. It is known that
the distributed Boolean function represented by M is hard to compute
in various restricted models of computation if the spectral norm is
bounded from above by N^(1-e), where e>0 denotes a fixed constant. For
instance, the size of a two-layer threshold circuit (with polynomially
bounded weights for the gates in the hidden layer, but unbounded
weights for the output gate) grows exponentially fast with n=log N. We
prove sufficient conditions on M that imply small spectral norms (and
thus high computational complexity in restricted models).
Our general results cover specific cases, where the matrix M
represents a bit (the least significant bit or other fixed bits) of
fundamental functions. Functions like the discrete multiplication and
division, as well as cryptographic functions such as the
Diffie-Hellman function and the decoding functions of the Pointcheval
and the ElGamal cryptosystems can be addressed by our technique.
In order to obtain our results, we make a detour on exponential sums
and on spectral norms of matrices with complex entries.
References:
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Ragesh Jaiswal, CSE, UCSD
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19 May, 11-12:20 pm, AP&M 5218
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Topic: Analysis of Hierarchical Markov Chains
Abstract: Markov chains provide useful algorithmic paradigm for approaching generation problems
in general. Analysing the rate of convergence of appropriate markov chain becomes the
core issue when working with these stochastic techniques. Various methods like coupling,
canonical paths, decomposition have been suggested to analyse the convergence rate of various
classes of markov chains. We are primarily interested in reversible, hierarchical markov
chains which comes up naturally for problems like Independent Set, Graph Matchings etc.
In this work we suggest a characterization which is useful in bounding the convergence rate of
a markov chain with a biased stationary distribution, in terms of the convergence rate
of the corresponding markov chain with unbiased (uniform) stationary distribution.
References:
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Josh Buresh-Oppenheim, CSE, UCSD
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12 May, 11-12:20pm, AP&M 5218
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Topic: Towards Models for Backtracking and Dynamic Programming
Abstract: Since most algorithms that people use can intuitively be classified into
large paradigms of algorithms such as greedy, dynamic programming, LP
rounding, local search, etc., it is natural to ask what problems can be
computed by these paradigms. This question can be seen as an alternative
to asking what problems can be computed by all, say, poly-time algorithms
in that the restriction on the algorithms is more conceptual rather than
complexity-theoretic. Of course, to ask a question about an algorithmic
paradigm, you first have to formally define the paradigm. We offer one
very natural model, BT, which captures many algorithms generally
considered to be dynamic programming or backtracking. This model is an
extension of the Priority Algorithm model of Borodin, Nielsen and Rackoff,
which captures greedy algorithms. We demonstrate many upper and lower
bounds in this model for problems such as interval scheduling, knapsack
and SAT. We then define a stronger model, DP, and show that it captures
some aspects of dynamic programming that BT does not.
References:
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Misha Alekhnovich, IAS Princeton
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6 May, 1-2pm, AP&M 4301
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Topic: The Hardness of the Closest Vector Problem for Pre-processed Lattices
Abstract: We show that, unless NP has quasipolynomial algorithms
the Closest Vector Problem with Pre-processing, for $\ell_p$ norm
for any $p \geq 1,$ is hard to approximate within a factor of
$(\log n)^{1/p-\epsilon}.$ This improves the previous best factor
$3^{1/p}$ due to Regev. Our results also imply that for any
$\epsilon>0,$ under the same complexity assumption, the Nearest Codeword
Problem with Pre-processing is hard to approximate within a factor of
$(\log n)^{1-\epsilon}.$
References:
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Dr. Alexei Ashikhmin , Bell Laboratories, Lucent Technologies
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10 May, 1-2pm, Fung Auditorium of the Powell-Focht Bioengineering
Hall at UCSD
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Topic: Quantum Codes: Constructions and Parameters
Abstract: It is well known that a number of computational problems
can be solved on a quantum computer exponentially faster than
on a classical computer. One of the main problems in building
a quantum computer is its unavoidable coupling with an environment.
This coupling results in decoherence of quantum states. The only
way of mitigating the decohernece is quantum error-correction.
In this talk, I will give a general introduction to quantum error
correcting codes. In particular, I will start with a definition of
a quantum code, its minimum distance, and its distance distribution.
After that, I will survey the state of our knowledge about quantum
codes, including best-known results concerning explicit constructions
of asymptotically-good quantum codes, upper and lower bounds on the
minimum distance of quantum codes, and the probability of undetected
error.
References:
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Daniele Micianccio, CSE, UCSD
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5 May, 11-12:20, AP&M 5218
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Topic: Pseudo Free Groups
Abstract:
References:
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Chris Calabro, CSE UCSD
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28 Apr, 11-12:20, AP&M 5218
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Topic: "The PCP theorem by gap amplification" (ECCC TR05-046)
Abstract: Let C={c_1,...,c_n} be a set of constraints over a set of variables.
The {em satisfiability-gap} of C is the smallest fraction of unsatisfied
constraints, ranging over all possible assignments for the variables. We
prove a new combinatorial amplification lemma that doubles the
satisfiability-gap of a constraint-system, with only a linear blowup in
the size of the system. Iterative application of this lemma yields a
self-contained (combinatorial) proof for the PCP theorem. The
amplification lemma relies on a new notion of "graph powering" that can
be applied to systems of constraints. This powering amplifies the
satisfiability-gap of a constraint system provided that the underlying
graph structure is an expander. We also apply the amplification lemma to
construct PCPs and locally-testable codes whose length is {em
quasi-linear}, and whose correctness can be probabilistically verified
by making a {em constant} number of queries. Namely, we prove SAT in
PCP_{0.5,1}[log(n * polylog n) , O(1)]. This answers an open question of
Ben-Sasson et al. (STOC '04).
References: http://www.eccc.uni-trier.de/eccc-reports/2005/TR05-046/index.html
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Yi-Kai Liu, CSE, UCSD
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21 Apr, 11-12, AP&M 5218
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Topic: Holographic algorithms" from FOCS 2004
Abstract: We introduce a new notion of efficient reduction among computational
problems. Classical reductions involve gadgets that map local solutions
of one problem to local solutions of another in one-to-one, or possibly
many-to-one or one-to-many, fashion. Our proposed reductions allow for
gadgets with many-to-many correspondences. Their objective is to
preserve the sum of the local solutions.
Such reductions provide a method of translating a combinatorial problem
to a family of finite systems of polynomial equations with integer
coefficients such that the number of solutions of the combinatorial
problem can be counted in polynomial time if some system in the family
has a solution over the complex numbers. We can derive polynomial time
algorithms in this way for ten problems for which only exponential time
algorithms were known before.
General questions about complexity classes are also formulated. If the
method is applied to a #P-complete problem then we obtain families of
polynomial systems such that the solvability of any one member would
imply P^(#P) = NC2.
References: http://ieeexplore.ieee.org/search/freesrchabstract.jsp? arnumber=1366250&isnumber=29918&
punumber=9430&k2dockey=1366250@ieeecnfs&query=%28%28 holographic+algorithms%29%3Cin%3Emetadata%29&pos=0
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Vadim Lyubashevski, CSE, UCSD
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14 Apr, 11-12, AP&M 5218
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Topic: Solving the Parity Problem with Few Examples and Decoding Random Linear Codes in Sub-Exponential Time
Abstract: A few years ago, Blum, Kalai and Wasserman demonstrated the first
sub-exponential algorithm for learning the parity function in the
presence of noise. They solved the length-n parity problem in
time 2^O(n/logn) but it required the availability of 2^O(n/logn)
labeled
examples. As an open problem, they asked whether there exists a
2^o(n) algorithm for the length-n parity problem that uses only poly(n)
labeled examples. In this talk, a positive answer will be provided.
It'll be shown that there is an algorithm that solves the length-n
parity
problem in time 2^O(n/loglogn) using n^(1+epsilon) labeled examples.
This result immediately gives us a sub-exponential algorithm for
decoding
n x n^(1+epsilon) random linear codes in the presence of random noise.
The same technique can also be used to come up with a sub-exponential
algorithm for dense instances of the random subset sum problem.
References:
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Shuchi Chawla, CMU
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11 Apr, 11-12, AP&M 4301
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Topic: Algorithms for Path-Planning
Abstract: Consider a robot with a map of its environment, that needs to visit
a number of sites to deliver packages, collect samples, etc. However, owing
to a limited supply of battery power, or some unforeseen obstacle, the robot
may not be able to visit all the sites. In such a situation, a natural
question is to ask for a tour that visits as many sites as possible by some
pre-determined deadline. This is the classic Orienteering problem. More
generally, path-planning problems involve a set of locations to be visited,
with constraints on the path taken to visit them, such as deadlines on
visiting particular locations, or a minimum number of locations that must be
visited. These problems arise in many fields including operations research,
scheduling, and robotics, and are mostly NP-hard. In this talk, Ms. Chawla
will present the first approximations to several path-planning problems
including Orienteering. Ms. Chawla will then discuss an application of
path-planning to robot navigation and describe the complications that arise
due to uncertainty in the robot's environment.
References:
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Sashka Davis, CSE, UCSD
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7 Apr, 11 - 12, AP&M 5218
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Topic: "Entropy Waves, the Zig-Zag Graph
Product, and New Constant-Degree Expanders" (O. Reingold, S. Vadhan, A. Wigderson, Annals of
Mathematics, Vol. 155, No.1, pp. 157-187, 2002.)
Abstract:
References:
http://www.math.ias.edu/~avi/PUBLICATIONS/MYPAPERS/ SALIL/EXPANDERS/ANNALS/paper.ps
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Salil Vadhan, Harvard University
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1 Apr, 2 - 3pm, AP&M 4301
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Topic: An Unconditional Study of Computational Zero Knowledge
Abstract: We prove a number of general theorems about ZK, the class of problems
possessing computational zero-knowledge proofs. Our results are
*unconditional*, in contrast to most previous works on ZK, which rely on
the assumption that one-way functions exist.
In particular, we show that:
- Honest-verifier ZK equals general ZK,
- Public-coin ZK equals private-coin ZK,
- ZK is closed under union, and
- ZK with imperfect completeness equals ZK with perfect completeness.
Our approach is to combine the conditional techniques previously used in
the study of ZK with the unconditional techniques that we and others
developed in the study of SZK, the class of problems possessing
statistical zero-knowledge proofs. To enable this combination, we prove
that every problem in ZK can be decomposed into a problem in SZK
together with a set of instances from which a one-way function can be
constructed.
References:
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Jia Mao, CSE, UCSD
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16 Mar, 1-2 pm, AP&M 4218
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Topic: Undirected ST-Connectivity in Log-Space, by Omer
Reingold.
Abstract: In this recent breakthrough paper, Reingold showed that USTCON, the
problem of whether there exists a path between two vertices in a given
undirected graph, is solvable by a deterministic log-space algorithm, thus
implying that SL = L as well as several other significant consequences.
References: http://www.wisdom.weizmann.ac.il/~reingold/publications/sl.ps
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Alan Nash, UCSD Math and CSE
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9 Mar, 1-2pm
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Topic: PTIME Queries Revisited: joint work with Jeff Remmel and Victor Vianu
Abstract: The existence of a language expressing precisely the PTIME queries on
arbitrary structures
remains the central open problem in the theory of database query languages.
As it turns out, two variants of this question have been formulated.
Surprisingly, despite the importance of the problem, the relationship between
these variants
has not been systematically explored.
A first contribution of the present paper is to revisit
the basic definitions and clarify the connection between these two variants.
We then investigate two relaxations
to the original problem that appear as tempting alternatives in the absence of
a language for
the PTIME queries. The first consists in trying to express the PTIME queries
using a richer language
that can also express queries beyond PTIME, but for which there exists
a query processor evaluating all PTIME queries in PTIME.
The second approach, studied by many researchers, is to focus on PTIME
properties on restricted sets of graphs.
Our results are mostly negative, and point out limitations to both approaches.
Finally, we turn to a natural class of languages that we call finitely
generated, whose syntax is obtained by
applying a fixed set of constructors to a given set of building blocks. We
identify
a broad class of such languages that cannot express all the PTIME queries.
References:
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William Matthews, UCSD
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2 march, 1-2 pm, AP&M 4218
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Topic: A Deterministic (2-2/(k+1))^n Algorithm
for k-SAT Based
on Local Search, by Dantsin, Goerdt, Hirsh, Kannan, Kleinberg,
Papadimitriou, Raghavan, and Schoning.
Abstract: Local search is widely used for solving the propositional satisfiability problem. Papadimitriou (1991) showed that randomized local search solves 2-SAT in polynomial time. Recently, Schöning (1999) proved that a close algorithm for k-SAT takes time (2 - 2/k)n up to a polynomial factor. This is the best known worst-case upper bound for randomized 3-SAT algorithms (cf. also recent preprint by Schuler et al.).We describe a deterministic local search algorithm for k-SAT running in time (2-2/(k+ 1))n up to a polynomial factor. The key point of our algorithm is the use of covering codes instead of random choice of initial assignments. Compared to other "weakly exponential" algorithms, our algorithm is technically quite simple. We also describe an improved version of local search. For 3-SAT the improved algorithm runs in time 1.481n up to a polynomial factor. Our bounds are better than all previous bounds for deterministic k-SAT algorithms.
References: http://portal.acm.org/citation.cfm?id=637765
http://portal.acm.org/citation.cfm?id=796524
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Russell Impagliazzo, UCSD
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23 Feb, 1:00 - 2:00, AP&M 4218
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Topic: Error-correcting codes and hardness amplification (Contd)
Abstract:
References:
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Russell Impagliazzo, UCSD
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16 Feb, 1 -2 PM, 4218 AP&M
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Topic: Error-correcting codes and hardness amplification
Abstract: In hardness amplification, we are given a worst-case hard problem or a problem hard for some small fraction of instances. We wish to construct a reliably hard problem, hard for almost all instances. Hardness amplification is important for cryptography and pseudo-randomness, in that one needs reliably hard problems for both types of application.
In hindsight, many of the techniques used for hardness amplification resemble those in error-correction. In fact, it is relatively
straight-forward to translate hardness amplification results into error-correction results. The result illuminates techniques in both areas. This talk will sketch the parallels
between hardness amplification and error-correction. It will also discuss a new type of
weak error-correction that arises from this viewpoint, a boosting code.
References: Note: references are from bad memory.
Yao, Theory and application of trap-door one-way functions.
Goldreich, Levin: A hard-core bit for any one-way function.
Babai, Fortnow, Nisan , Wigderson: P=BPP unless EXP has publishable proofs
Impagliazzo, Wigderson: P=BPP unless EXP has subexponential circuits.
Sudan, Trevisan, Vadhan: Derandomization through locally list-decoding
Trevisan's extractor paper.
Trevisan's new paper.
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James R. Lee, UC Berkeley
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11 Feb, 11:00 - 12:00, AP&M 4301
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Topic: Metric Geometry and Computer Science
Abstract:
References:
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Alexander Vardy, ECE, UC San Diego
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12:30 - 2:00, AP&M 4218
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Topic: Old Problems and New Results in Coding Theory
Abstract: Coding theory was born in 1948 with the work of Claude Shannon, who proved
that for every information rate $R$ up to channel capacity, there exists a
code of rate $R$ that guarantees a vanishing probability of decoding
error. Shannon, however, did not tell us how to find such codes nor how to
decode them.
It was recognized early on that codes with good Hamming distance can
correct many errors, while codes endowed with algebraic structure admit
efficient algebraic decoding algorithms. This has led to over 50 years of
research in algebraic and combinatorial coding theory. We will survey
several key problems and new results in this area. In particular, we'll
elaborate upon a new asymptotic improvement of the Gilbert-Varshamov bound
and upon recent methods for decoding Reed-Solomon codes using bivariate
polynomial interpolation.
About 10 years ago, the field of coding theory was transformed by the
discovery of codes defined on certain graphs, with no algebraic structure,
that perform extremely close to the Shannon capacity under probabilistic
message-passing decoding. We will briefly review this exciting
development, and point out the challenges that lie ahead in the area of
"probabilistic" coding theory.
References:
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