| 2025 | AISTATS | Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix. | Charles Margossian, Lawrence K. Saul |
| 2025 | AISTATS | Batch, match, and patch: low-rank approximations for score-based variational inference. | Chirag Modi, Diana Cai, Lawrence K. Saul |
| 2024 | ICML | 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 |
| 2023 | UAI | The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference. | Charles C. Margossian, Lawrence K. Saul |
| 2020 | PLDI | Generating correctness proofs with neural networks. | Alex Sanchez-Stern, Yousef Alhessi, Lawrence K. Saul, Sorin Lerner |
| 2020 | SIGMOD | SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data. | Vraj Shah, Side Li, Arun Kumar, Lawrence K. Saul |
| 2019 | DATE | "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 |
| 2019 | IMC | 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 |
| 2019 | SIGMOD | Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data. | Vraj Shah, Side Li, Kevin Yang, Arun Kumar, Lawrence K. Saul |
| 2018 | ICCD | Using Machine Learning to Predict Path-Based Slack from Graph-Based Timing Analysis. | Andrew B. Kahng, Uday Mallappa, Lawrence K. Saul |
| 2017 | SIGMOD | SpeakQL: Towards Speech-driven Multi-modal Querying. | Dharmil Chandarana, Vraj Shah, Arun Kumar, Lawrence K. Saul |
| 2015 | IMC | 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 |
| 2015 | IMC | Who is .com?: Learning to Parse WHOIS Records. | Suqi Liu, Ian D. Foster, Stefan Savage, Geoffrey M. Voelker, Lawrence K. Saul |
| 2014 | AISTATS | A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data. | Do-kyum Kim, Matthew F. Der, Lawrence K. Saul |
| 2014 | IMC | 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 |
| 2014 | KDD | Knock it off: profiling the online storefronts of counterfeit merchandise. | Matthew F. Der, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker |
| 2013 | ICML | A Variational Approximation for Topic Modeling of Hierarchical Corpora. | Do-kyum Kim, Geoffrey M. Voelker, Lawrence K. Saul |
| 2013 | NSDI | 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 |
| 2011 | CCS | 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 |
| 2011 | CCS | Topic modeling of freelance job postings to monitor web service abuse. | Do-kyum Kim, Marti Motoyama, Geoffrey M. Voelker, Lawrence K. Saul |
| 2010 | KDD | Beyond heuristics: learning to classify vulnerabilities and predict exploits. | Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker |
| 2009 | ASRU | Large-margin feature adaptation for automatic speech recognition. | Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul |
| 2009 | ICASSP | Sparse decomposition of mixed audio signals by basis pursuit with autoregressive models. | Youngmin Cho, Lawrence K. Saul |
| 2009 | ICML | Matrix updates for perceptron training of continuous density hidden Markov models. | Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul |
| 2009 | ICML | Learning dictionaries of stable autoregressive models for audio scene analysis. | Youngmin Cho, Lawrence K. Saul |
| 2009 | ICML | Identifying suspicious URLs: an application of large-scale online learning. | Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker |
| 2009 | Interspeech | A fast online algorithm for large margin training of continuous density hidden Markov models. | Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul |
| 2009 | KDD | Beyond blacklists: learning to detect malicious web sites from suspicious URLs. | Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker |
| 2008 | ICASSP | Nonnegative matrix factorization for real time musical analysis and sight-reading evaluation. | Chih-Chieh Cheng, D. Jingtong Hu, Lawrence K. Saul |
| 2008 | ICML | Fast solvers and efficient implementations for distance metric learning. | Kilian Q. Weinberger, Lawrence K. Saul |
| 2008 | ICMLA | Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data. | Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinberger, Lawrence K. Saul |
| 2007 | ICASSP | Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models. | Fei Sha, Lawrence K. Saul |
| 2007 | IDA | Multiplicative Updates for | Fei Sha, Y. Albert Park, Lawrence K. Saul |
| 2006 | AAAI | An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding. | Kilian Q. Weinberger, Lawrence K. Saul |
| 2006 | ICASSP | Large Margin Gaussian Mixture Modeling for Phonetic Classification and Recognition. | Fei Sha, Lawrence K. Saul |
| 2005 | AISTATS | Semisupervised alignment of manifolds. | Jihun Ham, Daniel D. Lee, Lawrence K. Saul |
| 2005 | AISTATS | Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization. | Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul |
| 2005 | ICML | Analysis and extension of spectral methods for nonlinear dimensionality reduction. | Fei Sha, Lawrence K. Saul |
| 2004 | CVPR | Unsupervised Learning of Image Manifolds by Semidefinite Programming. | Kilian Q. Weinberger, Lawrence K. Saul |
| 2004 | ICASSP | Exploratory analysis and visualization of speech and music by locally linear embedding. | Viren Jain, Lawrence K. Saul |
| 2004 | ICASSP | Nonnegative deconvolution for time of arrival estimation. | Yuanqing Lin, Daniel D. Lee, Lawrence K. Saul |
| 2004 | ICASSP | Multiband statistical learning for f | Fei Sha, John Ashley Burgoyne, Lawrence K. Saul |
| 2004 | ICML | Learning a kernel matrix for nonlinear dimensionality reduction. | Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul |
| 2004 | IMC | Modeling distances in large-scale networks by matrix factorization. | Yun Mao, Lawrence K. Saul |
| 2003 | AISTATS | A Generalized Linear Model for Principal Component Analysis of Binary Data. | Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar |
| 2003 | COLT | Multiplicative Updates for Large Margin Classifiers. | Fei Sha, Lawrence K. Saul, Daniel D. Lee |
| 2003 | Interspeech | Statistical signal processing with nonnegativity constraints. | Lawrence K. Saul, Fei Sha, Daniel D. Lee |
| 1999 | Interspeech | Modeling the rate of speech by Markov processes on curves. | Lawrence K. Saul, Mazin G. Rahim |
| 1998 | ICML | Automatic Segmentation of Continuous Trajectories with Invariance to Nonlinear Warpings of Time. | Lawrence K. Saul |
| 1998 | UAI | Large Deviation Methods for Approximate Probabilistic Inference. | Michael J. Kearns, Lawrence K. Saul |
| 1997 | AISTATS | Mixed Memory Markov Models. | Lawrence K. Saul, Michael I. Jordan |
| 1997 | EMNLP | Aggregate and mixed-order Markov models for statistical language processing. | Lawrence K. Saul, Fernando Pereira |
| 1996 | COLT | Learning Curve Bounds for a Markov Decision Process with Undiscounted Rewards. | Lawrence K. Saul, Satinder P. Singh |
| 1995 | COLT | Markov Decision Processes in Large State Spaces. | Lawrence K. Saul, Satinder P. Singh |