Lawrence K. Saul

According to our database, Lawrence K. Saul authored at least 119 papers between 1994 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

EigenVI: score-based variational inference with orthogonal function expansions.

Diana Cai, Chirag Modi, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

CoRR, 2024

Batch, match, and patch: low-rank approximations for score-based variational inference.

Chirag Modi, Diana Cai, Lawrence K. Saul

CoRR, 2024

Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix.

Charles C. Margossian, Lawrence K. Saul

CoRR, 2024

An Ordering of Divergences for Variational Inference with Factorized Gaussian Approximations.

Charles C. Margossian, Loucas Pillaud-Vivien, Lawrence K. Saul

CoRR, 2024

Batch and match: black-box variational inference with a score-based divergence.

Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Weight-balancing fixes and flows for deep learning.

Lawrence K. Saul

Trans. Mach. Learn. Res., 2023

The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference.

Charles C. Margossian, Lawrence K. Saul

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Variational Inference with Gaussian Score Matching.

Chirag Modi, Robert M. Gower, Charles Margossian, Yuling Yao, David M. Blei, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A geometrical connection between sparse and low-rank matrices and its application to manifold learning.

Lawrence K. Saul

Trans. Mach. Learn. Res., 2022

A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data.

Lawrence K. Saul

SIAM J. Math. Data Sci., 2022

Measuring security practices.

Louis F. DeKoven, Audrey Randall, Ariana Mirian, Gautam Akiwate, Ansel Blume, Lawrence K. Saul, Aaron Schulman, Geoffrey M. Voelker, Stefan Savage

Commun. ACM, 2022

2021

An EM Algorithm for Capsule Regression.

Lawrence K. Saul

Neural Comput., 2021

An online passive-aggressive algorithm for difference-of-squares classification.

Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data.

Vraj Shah, Side Li, Arun Kumar, Lawrence K. Saul

Proceedings of the 2020 International Conference on Management of Data, 2020

Generating correctness proofs with neural networks.

Alex Sanchez-Stern, Yousef Alhessi, Lawrence K. Saul, Sorin Lerner

Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2020

2019

Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data.

Vraj Shah, Side Li, Kevin Yang, Arun Kumar, Lawrence K. Saul

Proceedings of the 2019 International Conference on Management of Data, 2019

Measuring Security Practices and How They Impact Security.

Louis F. DeKoven, Audrey Randall, Ariana Mirian, Gautam Akiwate, Ansel Blume, Lawrence K. Saul, Aaron Schulman, Geoffrey M. Voelker, Stefan Savage

Proceedings of the Internet Measurement Conference, 2019

"Unobserved Corner" Prediction: Reducing Timing Analysis Effort for Faster Design Convergence in Advanced-Node Design.

Andrew B. Kahng, Uday Mallappa, Lawrence K. Saul, Shangyuan Tong

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

2018

Using Machine Learning to Predict Path-Based Slack from Graph-Based Timing Analysis.

Andrew B. Kahng, Uday Mallappa, Lawrence K. Saul

Proceedings of the 36th IEEE International Conference on Computer Design, 2018

2017

SpeakQL: Towards Speech-driven Multi-modal Querying.

Dharmil Chandarana, Vraj Shah, Arun Kumar, Lawrence K. Saul

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, 2017

HIV Risk on Twitter: the Ethical Dimension of Social Media Evidence-based Prevention for Vulnerable Populations.

Nadir Weibel, Purvi Desai, Lawrence K. Saul, Amarnath Gupta, Susan Little

Proceedings of the 50th Hawaii International Conference on System Sciences, 2017

2016

On the (In)effectiveness of Mosaicing and Blurring as Tools for Document Redaction.

Steven Hill, Zhimin Zhou, Lawrence K. Saul, Hovav Shacham

Proc. Priv. Enhancing Technol., 2016

Failure analysis and prediction for the CIPRES science gateway.

Kritika Singh, Shava Smallen, Sameer Tilak, Lawrence K. Saul

Concurr. Comput. Pract. Exp., 2016

2015

Who is .com?: Learning to Parse WHOIS Records.

Suqi Liu, Ian D. Foster, Stefan Savage, Geoffrey M. Voelker, Lawrence K. Saul

Proceedings of the 2015 ACM Internet Measurement Conference, 2015

From .academy to .zone: An Analysis of the New TLD Land Rush.

Tristan Halvorson, Matthew F. Der, Ian D. Foster, Stefan Savage, Lawrence K. Saul, Geoffrey M. Voelker

Proceedings of the 2015 ACM Internet Measurement Conference, 2015

2014

Topic Modeling of Hierarchical Corpora.

Do-kyum Kim, Geoffrey M. Voelker, Lawrence K. Saul

CoRR, 2014

Knock it off: profiling the online storefronts of counterfeit merchandise.

Matthew F. Der, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Search + Seizure: The Effectiveness of Interventions on SEO Campaigns.

David Y. Wang, Matthew F. Der, Mohammad Karami, Lawrence K. Saul, Damon McCoy, Stefan Savage, Geoffrey M. Voelker

Proceedings of the 2014 Internet Measurement Conference, 2014

A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data.

Do-kyum Kim, Matthew F. Der, Lawrence K. Saul

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

eDoctor: Automatically Diagnosing Abnormal Battery Drain Issues on Smartphones.

Xiao Ma, Peng Huang, Xinxin Jin, Pei Wang, Soyeon Park, Dongcai Shen, Yuanyuan Zhou, Lawrence K. Saul, Geoffrey M. Voelker

Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation, 2013

A Variational Approximation for Topic Modeling of Hierarchical Corpora.

Do-kyum Kim, Geoffrey M. Voelker, Lawrence K. Saul

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning.

Matthew F. Der, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Learning to detect malicious URLs.

Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

ACM Trans. Intell. Syst. Technol., 2011

Hidden-Unit Conditional Random Fields.

Laurens van der Maaten, Max Welling, Lawrence K. Saul

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Nonnegative Matrix Factorization for Semi-supervised Dimensionality Reduction

Youngmin Cho, Lawrence K. Saul

CoRR, 2011

Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification

Youngmin Cho, Lawrence K. Saul

CoRR, 2011

Maximum Covariance Unfolding : Manifold Learning for Bimodal Data.

Vijay Mahadevan, Chi Wah Wong, José Costa Pereira, Tom Liu, Nuno Vasconcelos, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Online learning of large margin hidden Markov models for automatic speech recognition.

Lawrence K. Saul, Chih-Chieh Cheng, Fei Sha

Proceedings of the 2011 Symposium on Machine Learning in Speech and Language Processing, 2011

Topic modeling of freelance job postings to monitor web service abuse.

Do-kyum Kim, Marti Motoyama, Geoffrey M. Voelker, Lawrence K. Saul

Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence, 2011

Judging a site by its content: learning the textual, structural, and visual features of malicious web pages.

Sushma Nagesh Bannur, Lawrence K. Saul, Stefan Savage

Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence, 2011

2010

Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner].

Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul

IEEE Signal Process. Mag., 2010

Large-Margin Classification in Infinite Neural Networks.

Youngmin Cho, Lawrence K. Saul

Neural Comput., 2010

Online Learning and Acoustic Feature Adaptation in Large-Margin Hidden Markov Models.

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul

IEEE J. Sel. Top. Signal Process., 2010

Exploiting Feature Covariance in High-Dimensional Online Learning.

Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, Fernando Pereira

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development.

Diane Hu, Laurens van der Maaten, Youngmin Cho, Lawrence K. Saul, Sorin Lerner

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Beyond heuristics: learning to classify vulnerabilities and predict exploits.

Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009

URL Reputation.

Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

Dataset, October, 2009

Distance Metric Learning for Large Margin Nearest Neighbor Classification.

Kilian Q. Weinberger, Lawrence K. Saul

J. Mach. Learn. Res., 2009

Technical perspective - The ultimate pilot program.

Stuart Russell, Lawrence K. Saul

Commun. ACM, 2009

Kernel Methods for Deep Learning.

Youngmin Cho, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Beyond blacklists: learning to detect malicious web sites from suspicious URLs.

Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

A Probabilistic Topic Model for Unsupervised Learning of Musical Key-Profiles.

Diane Hu, Lawrence K. Saul

Proceedings of the 10th International Society for Music Information Retrieval Conference, 2009

A fast online algorithm for large margin training of continuous density hidden Markov models.

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul

Proceedings of the 10th Annual Conference of the International Speech Communication Association, 2009

Identifying suspicious URLs: an application of large-scale online learning.

Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learning dictionaries of stable autoregressive models for audio scene analysis.

Youngmin Cho, Lawrence K. Saul

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Matrix updates for perceptron training of continuous density hidden Markov models.

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Sparse decomposition of mixed audio signals by basis pursuit with autoregressive models.

Youngmin Cho, Lawrence K. Saul

Proceedings of the IEEE International Conference on Acoustics, 2009

Large-margin feature adaptation for automatic speech recognition.

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul

Proceedings of the 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009

2008

Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data.

Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinberger, Lawrence K. Saul

Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Fast solvers and efficient implementations for distance metric learning.

Kilian Q. Weinberger, Lawrence K. Saul

Proceedings of the Machine Learning, 2008

Nonnegative matrix factorization for real time musical analysis and sight-reading evaluation.

Chih-Chieh Cheng, D. Jingtong Hu, Lawrence K. Saul

Proceedings of the IEEE International Conference on Acoustics, 2008

2007

Multiplicative Updates for Nonnegative Quadratic Programming.

Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee

Neural Comput., 2007

Multiplicative Updates for <i>L</i>₁-Regularized Linear and Logistic Regression.

Fei Sha, Y. Albert Park, Lawrence K. Saul

Proceedings of the Advances in Intelligent Data Analysis VII, 2007

Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models.

Fei Sha, Lawrence K. Saul

Proceedings of the IEEE International Conference on Acoustics, 2007

2006

IDES: An Internet Distance Estimation Service for Large Networks.

Yun Mao, Lawrence K. Saul, Jonathan M. Smith

IEEE J. Sel. Areas Commun., 2006

Unsupervised Learning of Image Manifolds by Semidefinite Programming.

Kilian Q. Weinberger, Lawrence K. Saul

Int. J. Comput. Vis., 2006

Graph Laplacian Regularization for Large-Scale Semidefinite Programming.

Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Large Margin Hidden Markov Models for Automatic Speech Recognition.

Fei Sha, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Large Margin Gaussian Mixture Modeling for Phonetic Classification and Recognition.

Fei Sha, Lawrence K. Saul

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding.

Kilian Q. Weinberger, Lawrence K. Saul

Proceedings of the Proceedings, 2006

Spectral Methods for Dimensionality Reduction.

Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, Daniel D. Lee

Proceedings of the Semi-Supervised Learning, 2006

2005

Distance Metric Learning for Large Margin Nearest Neighbor Classification.

Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Learning Harmonic Relationships in Digital Audio with Dirichlet-Based Hidden Markov Models.

John Ashley Burgoyne, Lawrence K. Saul

Proceedings of the ISMIR 2005, 2005

Analysis and extension of spectral methods for nonlinear dimensionality reduction.

Fei Sha, Lawrence K. Saul

Proceedings of the Machine Learning, 2005

Visualization of low Dimensional Structure in tonal pitch Space.

John Ashley Burgoyne, Lawrence K. Saul

Proceedings of the 2005 International Computer Music Conference, 2005

Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization.

Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Semisupervised alignment of manifolds.

Jihun Ham, Daniel D. Lee, Lawrence K. Saul

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization.

Fei Sha, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Hierarchical Distributed Representations for Statistical Language Modeling.

John Blitzer, Kilian Q. Weinberger, Lawrence K. Saul, Fernando Pereira

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Modeling distances in large-scale networks by matrix factorization.

Yun Mao, Lawrence K. Saul

Proceedings of the 4th ACM SIGCOMM Internet Measurement Conference, 2004

Learning a kernel matrix for nonlinear dimensionality reduction.

Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul

Proceedings of the Machine Learning, 2004

Multiband statistical learning for f₀ estimation in speech.

Fei Sha, John Ashley Burgoyne, Lawrence K. Saul

Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Nonnegative deconvolution for time of arrival estimation.

Yuanqing Lin, Daniel D. Lee, Lawrence K. Saul

Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Exploratory analysis and visualization of speech and music by locally linear embedding.

Viren Jain, Lawrence K. Saul

Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2003

Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifold.

Lawrence K. Saul, Sam T. Roweis

J. Mach. Learn. Res., 2003

Statistical signal processing with nonnegativity constraints.

Lawrence K. Saul, Fei Sha, Daniel D. Lee

Proceedings of the 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003, 2003

Multiplicative Updates for Large Margin Classifiers.

Fei Sha, Lawrence K. Saul, Daniel D. Lee

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

A Generalized Linear Model for Principal Component Analysis of Binary Data.

Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar

Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002

Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines.

Fei Sha, Lawrence K. Saul, Daniel D. Lee

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch.

Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell Jr., Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Robust numeric recognition in spoken language dialogue.

Mazin G. Rahim, Giuseppe Riccardi, Lawrence K. Saul, Jeremy H. Wright, Bruce Buntschuh, Allen L. Gorin

Speech Commun., 2001

A statistical model for robust integration of narrowband cues in speech.

Lawrence K. Saul, Mazin G. Rahim, Jont B. Allen

Comput. Speech Lang., 2001

Multiplicative Updates for Classification by Mixture Models.

Lawrence K. Saul, Daniel D. Lee

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Global Coordination of Local Linear Models.

Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000

Maximum likelihood and minimum classification error factor analysis for automatic speech recognition.

Lawrence K. Saul, Mazin G. Rahim

IEEE Trans. Speech Audio Process., 2000

Attractor Dynamics in Feedforward Neural Networks.

Lawrence K. Saul, Michael I. Jordan

Neural Comput., 2000

Markov Processes on Curves.

Lawrence K. Saul, Mazin G. Rahim

Mach. Learn., 2000

Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech.

Lawrence K. Saul, Jont B. Allen

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999

Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones.

Lawrence K. Saul, Michael I. Jordan

Mach. Learn., 1999

An Introduction to Variational Methods for Graphical Models.

Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul

Mach. Learn., 1999

Modeling the rate of speech by Markov processes on curves.

Lawrence K. Saul, Mazin G. Rahim

Proceedings of the Sixth European Conference on Speech Communication and Technology, 1999

1998

Large Deviation Methods for Approximate Probabilistic Inference.

Michael J. Kearns, Lawrence K. Saul

Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Markov Processes on Curves for Automatic Speech Recognition.

Lawrence K. Saul, Mazin G. Rahim

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Inference in Multilayer Networks via Large Deviation Bounds.

Michael J. Kearns, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Automatic Segmentation of Continuous Trajectories with Invariance to Nonlinear Warpings of Time.

Lawrence K. Saul

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

A Mean Field Learning Algorithm for Unsupervised Neural Networks.

Lawrence K. Saul, Michael I. Jordan

Proceedings of the Learning in Graphical Models, 1998

An Introduction to Variational Methods for Graphical Models.

Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul

Proceedings of the Learning in Graphical Models, 1998

1997

Modeling Acoustic Correlations by Factor Analysis.

Lawrence K. Saul, Mazin G. Rahim

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Aggregate and mixed-order Markov models for statistical language processing.

Lawrence K. Saul, Fernando Pereira

Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, 1997

Mixed Memory Markov Models.

Lawrence K. Saul, Michael I. Jordan

Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, 1997

1996

Mean Field Theory for Sigmoid Belief Networks.

Lawrence K. Saul, Tommi S. Jaakkola, Michael I. Jordan

J. Artif. Intell. Res., 1996

A Variational Principle for Model-based Morphing.

Lawrence K. Saul, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Hidden Markov Decision Trees.

Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Learning Curve Bounds for a Markov Decision Process with Undiscounted Rewards.

Lawrence K. Saul, Satinder P. Singh

Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995

Exploiting Tractable Substructures in Intractable Networks.

Lawrence K. Saul, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks.

Tommi S. Jaakkola, Lawrence K. Saul, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Markov Decision Processes in Large State Spaces.

Lawrence K. Saul, Satinder P. Singh

Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

1994

Learning in Boltzmann Trees.

Lawrence K. Saul, Michael I. Jordan

Neural Comput., 1994

Boltzmann Chains and Hidden Markov Models.

Lawrence K. Saul, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 7, 1994