Publications
[2016]
[2015]
[2014]
[2013]
[2012]
[2011]
[2010]
[2009]
[2008]
[2007]
[2006]
[2005]
[2004]
[2003]
[2002]
[2001]
[2000]
[1999]
[1998]
[1997]
[1996]
[1995]
[1994]
[1993]
[1992]
S. Hill, Z. Zhou, L. Saul, and H. Shacham (2016). On the (in)effectiveness of mosaicing and blurring as tools for document redaction. In Proceedings of the 16th Privacy Enhancing Technologies Symposium(PETS16), pages 404418. Darmstadt, Germany. [pdf]
S. Liu, I. Foster, S. Savage, G. M. Voelker, and L. K. Saul (2015). Who is .com? Learning to parse WHOIS records. In Proceedings of the ACM Internet Measurement Conference (IMC15), pages 369380. Tokyo, Japan.
[pdf]
T. Halvorson, M. F. Der, I. Foster, S. Savage, L. K. Saul, and G. M. Voelker (2015).
From .academy to .zone: an analysis of the new TLD land rush.
In Proceedings of the ACM Internet Measurement Conference (IMC15), pages 381394. Tokyo, Japan.
[pdf]
K. Singh, S. Smallen, S. Tilak, and L. K. Saul (2015). Failure analysis and prediction for the CIPRES science gateway. In Proceedings of the 10th Gateway Computing Environments Workshop (GCE15). Boulder, CO.
D. Wang, M. F. Der, M. Karami, L. K. Saul, D. McCoy, S. Savage, G. M. Voelker (2014). Search and seizure: the effectiveness of interventions on SEO campaigns. In Proceedings of the 2014 Internet Measurement Conference (IMC14), pages 359372. Vancouver, BC, Canada. [pdf]
M. F. Der, L. K. Saul, S. Savage, and G. M. Voelker (2014).
Knock it off: profiling the online storefronts of counterfeit merchandise. In Proceedings of the Twentieth ACM Conference on Knowledge Discovery and Data Mining (KDD14), pages 17591768.
New York, NY.
[pdf]
D.K. Kim, M. Der, and L. K. Saul (2014).
A Gaussian latent variable model for large margin classification of labeled and unlabeled data.
In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS14), pages 484492.
Reykjavik, Iceland.
[pdf]
[supplement]
[code]
D.K. Kim, G. M. Voelker, and L. K. Saul (2014). Topic modeling of hierarchical corpora.
[arxiv]
D.K. Kim, G. M. Voelker, and L. K. Saul (2013).
A variational approximation for topic modeling of hierarchical corpora. In Proceedings of the 30th International Conference
on Machine Learning (ICML13), pages 5563. Atlanta, GA.
[pdf]

X. Ma, P. Huang, X. Jin, P. Wang, S. Park, D. Shen, Y. Zhou, L. K. Saul, and G. M. Voelker (2013). eDoctor: automatically diagnosing abnormal battery drain issues on smartphones. In Proceedings of the 10th ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI13), pages 5770. Lombard, IL.
[pdf]

M. F. Der and L. K. Saul (2012).
Latent coincidence analysis: a hidden variable model for distance metric learning.
In P. Bartlett, F. C. N. Pereira, C. J. C. Burges, L. Bottou, K. Q. Weinberger (eds.), Advances in Neural Information Processing Systems 25, pages 32393247. Lake Tahoe, CA. [pdf]

V. Mahadevan, C.W. Wong, T. T. Liu, N. Vasconcelos and L. K. Saul (2011).
Maximum covariance unfolding: manifold learning for bimodal data.
In J. ShaweTaylor, R.S. Zemel, P. Bartlett, F. C. N. Pereira, and Culotta (eds.), Advances in Neural Information Processing Systems 24, pages 918926. Granada, Spain. [pdf]

S. N. Bannur, L. K. Saul, and S. Savage (2011).
Judging a site by its content: learning the textual, structural, and visual features of malicious Web pages.
In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC11), pages 110. Chicago, IL.
[pdf]

D.K. Kim, M. Motoyama, G. M. Voelker, and L. K. Saul (2011).
Topic modeling of freelance job postings to monitor web service abuse.
In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC11), pages 1120. Chicago, IL.
[pdf]

J. T. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2011).
Learning to detect malicious URLs.
ACM Transactions on Intelligent Systems and Technology 2(3),
pages 30:124.
[pdf]

L. J. P. van der Maaten, M. Welling, and L. K. Saul (2011). Hiddenunit conditional random fields. In Proceedings of the
Fourteenth International Conference on Artificial Intelligence & Statistics (AISTATS11), pages 479488. Fort Lauderdale, FL.
[pdf]
 D. J. Hu, L. van der Maaten, Y. Cho, L. K. Saul, and S. Lerner (2010). Latent variable models for predicting file dependencies in largescale software development. In J. Lafferty, C. K. I. Williams, J. ShaweTaylor, R.S. Zemel, and A. Culotta (eds.), Advances in Neural Information Processing Systems 23, pages 865873.
[pdf]

J. T. Ma, A. Kulesza, M. Dredze, K. Crammer, L. K. Saul, and F. C. N. Pereira (2010). Exploiting feature covariance in highdimensional online learning. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS10), pages 493500. Sardinia, Italy. [pdf]

K. Q. Weinberger, F. Sha, and L. K. Saul (2010). Convex optimizations for distance metric learning and pattern classification.
IEEE Signal Processing Magazine 27(3): 146158.
[pdf]
M. Bozorgi, L. K. Saul, S. Savage, and G. M. Voelker (2010).
Beyond heuristics: learning to classify vulnerabilities and predict exploits. In Proceedings of the Sixteenth ACM Conference on Knowledge Discovery and Data Mining (KDD10), pages 105113.
Washington, DC.
[pdf]
Y. Cho and L. K. Saul (2010).
Large margin classification in infinite neural networks. Neural Computation 22(10): 26782697. [pdf]

C.C. Cheng, F. Sha, and L. K. Saul (2010). Online learning and acoustic feature adaptation in large margin hidden Markov models.
IEEE Journal of Selected Topics in Signal Processing
4(6): 926942.
[pdf]
Y. Cho and L. K. Saul (2009).
Kernel methods for deep learning. In Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, and A. Culotta (eds.), Advances in Neural Information Processing Systems 22, pages 342350.
[pdf]
C.C. Cheng, F. Sha, and L. K. Saul (2009).
Large margin feature adaptation for automatic speech recognition. In Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU09), pages 8792.
Merano, Italy.
[pdf]
D. J. Hu and L. K. Saul (2009).
A probabilistic model of unsupervised learning for musicalkey profiles. In Proceedings of the Tenth International Society for Music Information Retrieval Conference (ISMIR09), pages 441446. Kobe, Japan.
[pdf]
C.C. Cheng, F. Sha, and L. K. Saul (2009).
A fast online algorithm for large margin training of continuousdensity hidden Markov models. In Proceedings of the Tenth Annual Conference of the International Speech Communication Association (Interspeech09), pages 668671.
Brighton, UK.
[pdf]
C.C. Cheng, F. Sha, and L. K. Saul (2009).
Matrix updates for perceptron training of continuousdensity hidden Markov models. In Proceedings of the Twenty Sixth International Conference on Machine Learning (ICML09), pages 153160. Montreal, Canada.
[pdf]
Y. Cho and L. K. Saul (2009). Learning dictionaries of stable autoregressive models for audio scene analysis. In Proceedings of the Twenty Sixth International Conference on Machine Learning (ICML09), pages 169176. Montreal, Canada.
[pdf]
Y. Cho and L. K. Saul (2009). Sparse decomposition of mixed audio signals by basis pursuit with autoregressive models.
In Proceedings of the International Conference of Acoustics, Speech, and Signal Processing (ICASSP09), pages 17051708. Taipei, Taiwan.
[pdf]
J. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2009).
Identifying suspicious URLs: an application of largescale online learning.
In Proceedings of the Twenty Sixth International Conference on Machine Learning (ICML09), pages 681688. Montreal, Canada.
[pdf]
J. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2009).
Beyond blacklists: learning to detect malicious web sites from suspicious URLs.
In Proceedings of the Fifthteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD09), pages 12451253. Paris, France.
[pdf]
S. Russell and L. K. Saul (2009). The ultimate pilot program. Communications of the ACM 52(7):96.
[pdf]
F. Sha and L. K. Saul (2009). Large margin training of continuousdensity hidden Markov models.
In J. Keshet and S. Bengio (eds.), Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, pages 101114. Wiley & Sons.
[pdf]
K. Q. Weinberger and L. K. Saul (2009). Distance metric learning for large margin nearest neighbor classification. Journal of Machine Learning Research 10:207244.
[pdf]
K. Q. Weinberger and L. K. Saul (2008). Fast solvers and efficient implementations for distance metric learning.
In Proceedings of the Twenty Fifth International Conference on Machine Learning (ICML08), pages 11601167. Helsinki, Finland.
[pdf]
C. C. Cheng, D. J. Hu, and L. K. Saul (2008).
Nonnegative matrix factorization for real time musical analysis and sightreading evaluation.
In Proceedings of the International Conference on
Acoustics, Speech, and Signal Processing (ICASSP08), pages 20172020. Las Vegas, NV.
[pdf]
J. M. Lewis, P. M. Hull, K. Q. Weinberger, and L. K. Saul (2008). Mapping uncharted waters: exploratory analysis, visualization, and clustering of oceanographic data.
In Proceedings of the Seventh International Conference on Machine Learning and Applications (ICMLA08), pages 388395. San Diego, CA.
[pdf]
J. Matteson, C. K. Kha, D. J. Hu, C. C. Cheng, L. K. Saul, and G. R. Sadler (2008). Campus community partnerships with people who are deaf or hard of hearing.
Assistive Technology Outcomes and Benefits 5(1): 2944.
[pdf]
F. Sha, Y. A. Park, and L. K. Saul (2007). Multiplicative updates for l1regularized linear and logistic regression.
In Proceedings of the Seventh Symposium on Intelligent Data Analysis (IDA07), pages 1324. 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 (ICASSP07), pages 313316. 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): 20042031.
[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 12491456. 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 largescale semidefinite programming.
In B. Schoelkopf, J. Platt, and T. Hofmann (eds.), Advances in Neural Information Processing Systems 19, pages 14891496. MIT Press: Cambridge, MA.
[pdf]
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): 22732284. [pdf]
K. Q. Weinberger and L. K. Saul (2006).
Unsupervised learning of image manifolds by semidefinite programming. International Journal of Computer Vision 70(1): 7790.
[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 (AAAI06), pages 16831686. 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 (ICASSP06), pages 265268. 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 14731480.
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, pages 293308. MIT Press: Cambridge, MA.
[pdf]
J. A. Burgoyne and L. K. Saul (2005).
Learning harmonic relationships in digital audio with Dirichletbased hidden Markov models.
In Proceedings of the Sixth International Conference on Music Information Retrieval
(ISMIR05), pages 438443. 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 (ICMC05), pages 243246.
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 (ICML05),
pages 785792. 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 381388. 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 120127. Barbados, West Indies.
[pdf]
F. Sha and L. K. Saul (2005).
Realtime 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 12331240.
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 185192.
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]

Y. Mao and L. K. Saul (2004).
Modeling distances in largescale networks by matrix factorization.
In Proceedings of the Second Internet Measurement
Conference (IMC04), pages 278287. 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
(ICML04), pages 839846. 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 (CVPR04), vol. 2, pages 988995. 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 (ICASSP04),
vol. 3, pages 984987. 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 (ICASSP04), vol. 2, pages 377380. Montreal, Canada.
[pdf]
F. Sha, J. A. Burgoyne, and L. K. Saul (2004).
Multiband statistical learning for f_{0} estimation in speech.
In Proceedings of the International Conference of
Speech, Acoustics, and Signal Processing (ICASSP04), vol. 5, pages 661664. 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]
L. K. Saul and S. T. Roweis (2003).
Think globally, fit locally: unsupervised learning of low dimensional manifolds.
Journal of Machine Learning Research 4:119155.
[ 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 10011004, 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 3441, 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 188202, 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 1421, 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 12051212. 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 10651073. MIT Press:
Cambridge, MA.
[pdf]
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 889896. 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 897904.
MIT Press: Cambridge, MA.
[ps.gz]
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): 175194.
[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(12): 195212.
[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 807813. MIT Press:
Cambridge, MA.
[pdf]
M. I. Jordan, Z. Ghahramani, T. Jaakkola, and L. K. Saul (1999).
An introduction to variational methods in graphical models.
Machine Learning 37(2): 183233.
[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): 7587.
[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):115125.
[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 415418, 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 751757. MIT Press: Cambridge, MA.
[pdf]
[errata]
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 260266. 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 105162.
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 541554.
MIT Press: Cambridge, MA.
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 311319. 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 749756. 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 506514, Madison, WI.
L. K. Saul and F. C. N. Pereira (1997).
Aggregate and mixedorder 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 8189. 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 (AISTATS97), 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 501507.
MIT Press: Cambridge, MA.
[pdf]
L. K. Saul and M. I. Jordan (1997).
A variational principle for modelbased morphing.
In M. C. Mozer, M. I. Jordan, and T. Petsche (eds.),
Advances in Neural Information Processing Systems 9,
pages 267273. MIT Press: Cambridge, MA.
[pdf]
L. K. Saul, T. Jaakkola, and M. Jordan (1996).
Mean field theory for sigmoid belief networks.
Journal of Artificial Intelligence Research 4:6176.
[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 486492. 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 147156. 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 528534.
MIT Press: Cambridge, MA.
[pdf]
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 435442.
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 281288. ACM Press, New York, NY.

