2007

• F. Sha, Y. A. Park, and L. K. Saul (2007). Multiplicative updates for l1-regularized linear and logistic regression. In Proceedings of the Seventh Symposium on Intelligent Data Analysis (IDA-07), pages 13-24. Ljubljana, Slovenia. [pdf]

• F. Sha and L. K. Saul (2007). Comparison of large margin training to other discriminative methods for phonetic recognition by hidden Markov models. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP-07), pages 313-316. Honolulu, HI. [pdf]

• F. Sha, Y. Lin, L. K. Saul, and D. D. Lee (2007). Multiplicative updates for nonnegative quadratic programming. Neural Computation 19(8): 2004-2031. [pdf]

• F. Sha and L. K. Saul (2007). Large margin hidden Markov models for automatic speech recognition. In B. Schoelkopf, J. Platt, and T. Hofmann (eds.), Advances in Neural Information Processing Systems 19, pages 1249-1456. MIT Press: Cambridge, MA. Outstanding student paper award. [pdf]

• K. Q. Weinberger, F. Sha, Q. Zhu, and L. K. Saul (2007). Graph Laplacian regularization for large-scale semidefinite programming. To appear in B. Schoelkopf, J. Platt, and T. Hofmann (eds.), Advances in Neural Information Processing Systems 19, pages 1489-1496. MIT Press: Cambridge, MA. [pdf]

2006

• Y. Mao, L. K. Saul and J. M. Smith (2006). IDES: An Internet distance estimation service for large networks. IEEE Journal On Selected Areas in Communications (JSAC), Special Issue on Sampling the Internet, Techniques and Applications, 24(12): 2273-2284. [pdf]

• K. Q. Weinberger and L. K. Saul (2006). Unsupervised learning of image manifolds by semidefinite programming. International Journal of Computer Vision 70(1): 77-90. [pdf]

• K. Q. Weinberger and L. K. Saul (2006). An introduction to nonlinear dimensionality reduction by maximum variance unfolding. In Proceedings of the Twenty First National Conference on Artificial Intelligence (AAAI-06), Boston, MA. [pdf]

• F. Sha and L. K. Saul (2006). Large margin Gaussian mixture modeling for phonetic classification and recognition. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP-06), pages 265-268. Toulouse, France. [pdf]

• K. Q. Weinberger, J. Blitzer, and L. K. Saul (2006). Distance metric learning for large margin nearest neighbor classification. In Y. Weiss, B. Schoelkopf, and J. Platt (eds.), Advances in Neural Information Processing Systems 18, pages 1473--1480. MIT Press: Cambridge, MA. [pdf]

• L. K. Saul, K. Q. Weinberger, J. H. Ham, F. Sha, and D. D. Lee (2006). Spectral methods for dimensionality reduction. In O. Chapelle, B. Schoelkopf, and A. Zien (eds.), Semisupervised Learning. MIT Press: Cambridge, MA. [pdf]

2005

• J. A. Burgoyne and L. K. Saul (2005). Learning harmonic relationships in digital audio with Dirichlet-based hidden Markov models. In Proceedings of the Sixth International Conference on Music Information Retrieval (ISMIR-05), pages 438-443. London, England. [pdf]

• J. A. Burgoyne and L. K. Saul (2005). Visualization of low dimensional structure in tonal pitch space. In Proceedings of the International Computer Music Conference (ICMC-05), pages 243-246. Barcelona, Spain. [pdf]

• F. Sha and L. K. Saul (2005). Analysis and extension of spectral methods for nonlinear dimensionality reduction. In Proceedings of the Twenty Second International Conference on Machine Learning (ICML-05), pages 785-792. Bonn, Germany. [pdf]

• K. Q. Weinberger, B. D. Packer, and L. K. Saul (2005). Nonlinear dimensionality reduction by semidefinite programming and kernel matrix factorization. In Z. Ghahramani and R. Cowell (eds.), Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, pages 381-388. Barbados, West Indies. Best student paper award. [pdf]

• J. H. Ham, D. D. Lee, and L. K. Saul (2005). Semisupervised alignment of manifolds. In Z. Ghahramani and R. Cowell (eds.), Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, pages 120-127. Barbados, West Indies. [pdf]

• F. Sha and L. K. Saul (2005). Real-time pitch determination of one or more voices by nonnegative matrix factorization. In L. K. Saul, Y. Weiss, and L. Bottou (eds.), Advances in Neural Information Processing Systems 17, pages 1233-1240. MIT Press: Cambridge, MA. [pdf]

• J. Blitzer, K. Q. Weinberger, L. K. Saul, and F. C. N. Pereira (2005). Hierarchical distributed representations for statistical language models. In L. K. Saul, Y. Weiss, and L. Bottou (eds.), Advances in Neural Information Processing Systems 17, pages 185-192. MIT Press: Cambridge, MA. [pdf]

• L. K. Saul, Y. Weiss, and L. Bottou (eds.) (2005). Advances in Neural Information Processing Systems 17: Proceedings of the 2004 Conference, MIT Press: Cambridge, MA. [index]

2004

• Y. Mao and L. K. Saul (2004). Modeling distances in large-scale networks by matrix factorization. In Proceedings of the Second Internet Measurement Conference (IMC-04), pages 278-287. Sicily, Italy. [pdf]

• K. Q. Weinberger, F. Sha, and L. K. Saul (2004). Learning a kernel matrix for nonlinear dimensionality reduction. In Proceedings of the Twenty First International Confernence on Machine Learning (ICML-04), pages 839-846. Banff, Canada. Outstanding student paper award. [pdf, matlab]

• K. Q. Weinberger and L. K. Saul (2004). Unsupervised learning of image manifolds by semidefinite programming. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-04), vol. 2, pages 988-995. Washington D.C. Outstanding student paper award. [pdf, matlab]

• V. Jain and L. K. Saul (2004). Exploratory analysis and visualization of speech and music by locally linear embedding. In Proceedings of the International Conference of Speech, Acoustics, and Signal Processing (ICASSP-04), vol. 3, pages 984-987. Montreal, Canada. [pdf]

• Y. Lin, D. D. Lee, and L. K. Saul (2004). Nonnegative deconvolution for time of arrival estimation. In Proceedings of the International Conference of Speech, Acoustics, and Signal Processing (ICASSP-04), vol. 2, pages 377-380. Montreal, Canada. [pdf]

• F. Sha, J. A. Burgoyne, and L. K. Saul (2004). Multiband statistical learning for f₀ estimation in speech. In Proceedings of the International Conference of Speech, Acoustics, and Signal Processing (ICASSP-04), vol. 5, pages 661-664. Montreal, Canada. [pdf]

• S. Thrun, L. K. Saul, and B. Schoelkopf (eds.) (2004). Advances in Neural Information Processing Systems 16, MIT Press: Cambridge, MA. [index]

2003

• L. K. Saul and S. T. Roweis (2003). Think globally, fit locally: unsupervised learning of low dimensional manifolds. Journal of Machine Learning Research 4:119-155. [ ps.gz, pdf, matlab]

• L. K. Saul, F. Sha, and D. D. Lee (2003). Statistical signal processing with nonnegativity constraints. In Proceedings of the Eighth European Conference on Speech Communication and Technology, volume 2, pages 1001-1004, Geneva, Switzerland. [pdf]

• J. H. Ham, D. D. Lee, and L. K. Saul (2003). Learning high dimensional correspondences from low dimensional manifolds. In Proceedings of the ICML 2003 Workshop on The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, pages 34-41, Washington, D.C. [pdf]

• F. Sha, L. K. Saul, and D. D. Lee (2003). Multiplicative updates for large margin classifiers. In Proceedings of the Sixteenth Annual Conference on Computational Learning Theory, pages 188-202, Washington D.C. [pdf]

• A. I. Schein, L. K. Saul, and L. Ungar (2003). A generalized linear model for principal component analysis of binary data. In C. M. Bishop and B. J. Frey (eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, pages 14-21, Key West, FL. [pdf]

• L. K. Saul, D. D. Lee, C. L. Isbell, and Y. LeCun (2003). Real time voice processing with audiovisual feedback: toward autonomous agents with perfect pitch. In S. Becker, S. Thrun, and K. Obermayer (eds.), Advances in Neural Information Processing Systems 15, pages 1205-1212. MIT Press: Cambridge, MA. [pdf, matlab]

• F. Sha, L. K. Saul, and D. D. Lee (2003). Multiplicative updates for nonnegative quadratic programming in support vector machines. In S. Becker, S. Thrun, and K. Obermayer (eds.), Advances in Neural Information Processing Systems 15, pages 1065-1073. MIT Press: Cambridge, MA. [pdf]

2002

• S. T. Roweis, L. K. Saul and G. E. Hinton (2002). Global coordination of locally linear models. In T. G. Dietterich, S. Becker, and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems 14, pages 889-896. MIT Press: Cambridge, MA. [ps.gz]

• L. K. Saul and D. D. Lee (2002). Multiplicative updates for classification by mixture models. In T. G. Dietterich, S. Becker, and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems 14, pages 897-904. MIT Press: Cambridge, MA. [ps.gz]

2001

• L. K. Saul, M. G. Rahim, and J. B. Allen (2001). A statistical model for robust integration of narrowband cues in speech. Computer Speech and Language 15(2): 175-194. [abstract, pdf]

• M. G. Rahim, G. Riccardi, L. K. Saul, J. Wright, B. Buntschuh, and A. Gorin (2001). Robust numeric recognition in spoken language dialogue. Speech Communication 34(1-2): 195-212. [abstract, pdf]

• L. K. Saul and J. B. Allen (2001). Periodic component analysis: an eigenvalue method for representing periodic structure in speech. In T. K. Leen, T. G. Dietterich, and V. Tresp (eds.), Advances in Neural Information Processing Systems 13, pages 807-813. MIT Press: Cambridge, MA. [pdf]

2000

• S. T. Roweis and L. K. Saul (2000). Nonlinear dimensionality reduction by locally linear embedding. Science 290: 2323-2326. [abstract, html, pdf, matlab]

• L. K. Saul and M. G. Rahim (2000). Markov processes on curves. Machine Learning 41(3): 345-363. [abstract]

• L. K. Saul and M. I. Jordan (2000). Attractor dynamics in feedforward neural networks. Neural Computation 12(6): 1313-1335. [abstract, pdf]

1999

• M. I. Jordan, Z. Ghahramani, T. Jaakkola, and L. K. Saul (1999). An introduction to variational methods in graphical models. Machine Learning 37(2): 183-233. [abstract]

• L. K. Saul and M. I. Jordan (1999). Mixed memory Markov models: decomposing complex stochastic processes as mixtures of simpler ones. Machine Learning 37(1): 75-87. [pdf]

• L. K. Saul and M. G. Rahim (1999). Maximum likelihood and minimum classification error factor analysis for automatic speech recognition. IEEE Transactions on Speech and Audio Processing 8(2):115-125. [pdf]

• L. K. Saul, M. G. Rahim, and J. B. Allen (1999). Learning from examples in critical bands of speech. In Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, Keystone, CO.

• L. K. Saul and M. G. Rahim (1999). Modeling the rate of speech by Markov processes on curves. In Proceedings of the Sixth European Conference on Speech Communication and Technology, pages 415-418, Budapest, Hungary.

• L. K. Saul and M. G. Rahim (1999). Markov processes on curves for automatic speech recognition. In M. S. Kearns, S. A. Solla, and D. A. Cohn (eds.), Advances in Neural Information Processing Systems 11, pages 751-757. MIT Press: Cambridge, MA.

• M. S. Kearns and L. K. Saul (1999). Inference in multilayer networks via large deviation bounds. In M. S. Kearns, S. A. Solla, and D. A. Cohn (eds.), Advances in Neural Information Processing Systems 11, pages 260-266. MIT Press: Cambridge, MA. [pdf]

• M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul (1999). An introduction to variational methods for graphical models. In M. I. Jordan (ed.), Learning in Graphical Models, pages 105-162. MIT Press: Cambridge, MA.

• L. K. Saul and M. I. Jordan (1999). A mean field learning algorithm for unsupervised neural networks. In M. I. Jordan (ed.), Learning in Graphical Models, pages 541-554. MIT Press: Cambridge, MA.

1998

• M. S. Kearns and L. K. Saul (1998). Large deviation methods for approximate probabilistic inference. In G. Cooper and S. Moral (eds.), Proceedings of the Fourteenth Annual Conference on Uncertainty in Artificial Intelligence, pages 311-319. Morgan Kaufmann: San Mateo, CA. [pdf]

• L. K. Saul and M. G. Rahim (1998). Modeling acoustic correlations by factor analysis. In M. I. Jordan, M. S. Kearns, and S. A. Solla (eds.), Advances in Neural Information Processing Systems 10, pages 749-756. MIT Press: Cambridge, MA.

• L. K. Saul and M. G. Rahim (1998). Automatic segmentation of continuous trajectories with invariance to nonlinear warpings of time. In J. Shavlik (ed.), Proceedings of the Fifteenth International Conference on Machine Learning, pages 506-514, Madison, WI.

1997

• L. K. Saul and F. C. N. Pereira (1997). Aggregate and mixed-order Markov models for statistical language processing. In C. Cardie and R. Weischedel (eds.), Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, pages 81-89. ACM Press, New York, NY. [pdf]

• L. K. Saul and M. I. Jordan (1997). Mixed memory Markov models. In P. Smyth and D. Madigan (eds.), Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, Fort Lauderdale, FL.

• M. I. Jordan, Z. Ghahramani, and L. K. Saul (1997). Hidden Markov decision trees. In M. C. Mozer, M. I. Jordan, and T. Petsche (eds.), Advances in Neural Information Processing Systems 9, pages 501-507. MIT Press: Cambridge, MA. [pdf]

• L. K. Saul and M. I. Jordan (1997). A variational principle for model-based morphing. In M. C. Mozer, M. I. Jordan, and T. Petsche (eds.), Advances in Neural Information Processing Systems 9, pages 267-273. MIT Press: Cambridge, MA. [pdf]

1996

• L. K. Saul, T. Jaakkola, and M. Jordan (1996). Mean field theory for sigmoid belief networks. Journal of Artificial Intelligence Research 4:61-76. [abstract, ps.Z, pdf]

• L. K. Saul and M. I. Jordan (1996). Exploiting tractable substructures in intractable networks. In D. S. Touretzky, M. C. Mozer, and S. E. Hasselmo (eds.), Advances in Neural Information Processing Systems 8, pages 486-492. MIT Press: Cambridge, MA. [pdf]

• L. K. Saul and S. Singh (1996). Learning curve bounds for Markov decision processes with undiscounted rewards. In Proceedings of the Ninth Annual Workshop on Computational Learning Theory, pages 147-156. ACM Press: New York, NY. [pdf]

• T. Jaakkola, L. K. Saul, and M. I. Jordan (1996). Fast learning by bounding likelihoods in sigmoid type belief networks. In D. S. Touretzky, M. C. Mozer, and S. E. Hasselmo (eds.), Advances in Neural Information Processing Systems 8, pages 528-534. MIT Press: Cambridge, MA. [pdf]

1995

• L. K. Saul and M. I. Jordan (1995). Boltzmann chains and hidden Markov models. In G. Tesauro, D. S. Touretzky, and T. K. Leen (eds.), Advances in Neural Information Processing Systems 7, pages 435-442. MIT Press: Cambridge, MA. [pdf]

• L. K. Saul and S. Singh (1995). Markov decision processes in large state spaces. In Proceedings of the Eighth Annual Workshop on Computational Learning Theory, pages 281-288. ACM Press, New York, NY.

1994

• L. K. Saul (1994). Exact Computations in the Statistical Mechanics of Disordered Systems. Phd Thesis, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA.

• L. K. Saul and M. I. Jordan (1994). Learning in Boltzmann trees. Neural Computation 6(6): 1174-1184. [pdf]

• L. K. Saul and M. Kardar (1994). The 2d ±J Ising spin glass: exact partition functions in polynomial time. Nuclear Physics B 432: 641-667.

1993

• L. K. Saul and M. Kardar (1993). Exact integer algorithm for the 2d ±J Ising spin glass. Physical Review E 48:R3221-3224.

1992

• L. K. Saul, M. Kardar, and N. Read (1992). Directed waves in random media. Physical Review A 45: 8859-8869.

• L. K. Saul (1992). Renormalization group for canted magnets. Physical Review B 46: 13487-13581.