Lawrence K. Saul

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 22

Top Venues

CoRR

Internet Measurement Conference

SIGMOD Conference

Trans. Mach. Learn. Res.

Publications

Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
Batch and match: black-box variational inference with a score-based divergence. CoRR (2024)
Charles C. Margossian, Loucas Pillaud-Vivien, Lawrence K. Saul
An Ordering of Divergences for Variational Inference with Factorized Gaussian Approximations. CoRR (2024)
Charles C. Margossian, Lawrence K. Saul
The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference. UAI (2023)
Lawrence K. Saul
Weight-balancing fixes and flows for deep learning. Trans. Mach. Learn. Res. 2023 (2023)
Chirag Modi, Robert Gower, Charles Margossian, Yuling Yao, David M. Blei, Lawrence K. Saul
Variational Inference with Gaussian Score Matching. NeurIPS (2023)
Chirag Modi, Charles Margossian, Yuling Yao, Robert Gower, David M. Blei, Lawrence K. Saul
Variational Inference with Gaussian Score Matching. CoRR (2023)
Lawrence K. Saul
A geometrical connection between sparse and low-rank matrices and its application to manifold learning. Trans. Mach. Learn. Res. 2022 (2022)
Lawrence K. Saul
A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data. SIAM J. Math. Data Sci. 4 (2) (2022)
Louis F. DeKoven, Audrey Randall, Ariana Mirian, Gautam Akiwate, Ansel Blume, Lawrence K. Saul, Aaron Schulman, Geoffrey M. Voelker, Stefan Savage
Measuring security practices. Commun. ACM 65 (9) (2022)
Lawrence K. Saul
An EM Algorithm for Capsule Regression. Neural Comput. 33 (1) (2021)
Lawrence K. Saul
An online passive-aggressive algorithm for difference-of-squares classification. NeurIPS (2021)
Alex Sanchez-Stern, Yousef Alhessi, Lawrence K. Saul, Sorin Lerner
Generating correctness proofs with neural networks. MAPL@PLDI (2020)
Vraj Shah, Side Li, Arun Kumar, Lawrence K. Saul
SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data. SIGMOD Conference (2020)
Andrew B. Kahng, Uday Mallappa, Lawrence K. Saul, Shangyuan Tong
"Unobserved Corner" Prediction: Reducing Timing Analysis Effort for Faster Design Convergence in Advanced-Node Design. DATE (2019)
Alex Sanchez-Stern, Yousef Alhessi, Lawrence K. Saul, Sorin Lerner
Generating Correctness Proofs with Neural Networks. CoRR (2019)
Louis F. DeKoven, Audrey Randall, Ariana Mirian, Gautam Akiwate, Ansel Blume, Lawrence K. Saul, Aaron Schulman, Geoffrey M. Voelker, Stefan Savage
Measuring Security Practices and How They Impact Security. Internet Measurement Conference (2019)
Vraj Shah, Side Li, Kevin Yang, Arun Kumar, Lawrence K. Saul
Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data. SIGMOD Conference (2019)
Andrew B. Kahng, Uday Mallappa, Lawrence K. Saul
Using Machine Learning to Predict Path-Based Slack from Graph-Based Timing Analysis. ICCD (2018)
Nadir Weibel, Purvi Desai, Lawrence K. Saul, Amarnath Gupta, Susan Little
HIV Risk on Twitter: the Ethical Dimension of Social Media Evidence-based Prevention for Vulnerable Populations. HICSS (2017)
Dharmil Chandarana, Vraj Shah, Arun Kumar, Lawrence K. Saul
SpeakQL: Towards Speech-driven Multi-modal Querying. HILDA@SIGMOD (2017)
Kritika Singh, Shava Smallen, Sameer Tilak, Lawrence K. Saul
Failure analysis and prediction for the CIPRES science gateway. Concurr. Comput. Pract. Exp. 28 (7) (2016)
Steven Hill, Zhimin Zhou, Lawrence K. Saul, Hovav Shacham
On the (In)effectiveness of Mosaicing and Blurring as Tools for Document Redaction. Proc. Priv. Enhancing Technol. 2016 (4) (2016)
Tristan Halvorson, Matthew F. Der, Ian D. Foster, Stefan Savage, Lawrence K. Saul, Geoffrey M. Voelker
From .academy to .zone: An Analysis of the New TLD Land Rush. Internet Measurement Conference (2015)
Suqi Liu, Ian D. Foster, Stefan Savage, Geoffrey M. Voelker, Lawrence K. Saul
Who is .com?: Learning to Parse WHOIS Records. Internet Measurement Conference (2015)
Matthew F. Der, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Knock it off: profiling the online storefronts of counterfeit merchandise. KDD (2014)
David Y. Wang, Matthew F. Der, Mohammad Karami, Lawrence K. Saul, Damon McCoy, Stefan Savage, Geoffrey M. Voelker
Search + Seizure: The Effectiveness of Interventions on SEO Campaigns. Internet Measurement Conference (2014)
Do-kyum Kim, Geoffrey M. Voelker, Lawrence K. Saul
Topic Modeling of Hierarchical Corpora. CoRR (2014)
Do-kyum Kim, Matthew F. Der, Lawrence K. Saul
A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data. AISTATS (2014)
Do-kyum Kim, Geoffrey M. Voelker, Lawrence K. Saul
A Variational Approximation for Topic Modeling of Hierarchical Corpora. ICML (2) (2013)
Michael J. Kearns, Lawrence K. Saul
Large Deviation Methods for Approximate Probabilistic Inference CoRR (2013)
Xiao Ma, Peng Huang, Xinxin Jin, Pei Wang, Soyeon Park, Dongcai Shen, Yuanyuan Zhou, Lawrence K. Saul, Geoffrey M. Voelker
eDoctor: Automatically Diagnosing Abnormal Battery Drain Issues on Smartphones. NSDI (2013)
Matthew F. Der, Lawrence K. Saul
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning. NIPS (2012)
Youngmin Cho, Lawrence K. Saul
Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification CoRR (2011)
Do-kyum Kim, Marti Motoyama, Geoffrey M. Voelker, Lawrence K. Saul
Topic modeling of freelance job postings to monitor web service abuse. AISec (2011)
Youngmin Cho, Lawrence K. Saul
Nonnegative Matrix Factorization for Semi-supervised Dimensionality Reduction CoRR (2011)
Sushma Nagesh Bannur, Lawrence K. Saul, Stefan Savage
Judging a site by its content: learning the textual, structural, and visual features of malicious web pages. AISec (2011)
Laurens van der Maaten, Max Welling, Lawrence K. Saul
Hidden-Unit Conditional Random Fields. AISTATS (2011)
Lawrence K. Saul, Chih-Chieh Cheng, Fei Sha
Online learning of large margin hidden Markov models for automatic speech recognition. MLSLP (2011)
Vijay Mahadevan, Chi Wah Wong, José Costa Pereira, Tom Liu, Nuno Vasconcelos, Lawrence K. Saul
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data. NIPS (2011)
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Learning to detect malicious URLs. ACM Trans. Intell. Syst. Technol. 2 (3) (2011)
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner]. IEEE Signal Process. Mag. 27 (3) (2010)
Diane Hu, Laurens van der Maaten, Youngmin Cho, Lawrence K. Saul, Sorin Lerner
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development. NIPS (2010)
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Beyond heuristics: learning to classify vulnerabilities and predict exploits. KDD (2010)
Youngmin Cho, Lawrence K. Saul
Large-Margin Classification in Infinite Neural Networks. Neural Comput. 22 (10) (2010)
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
Online Learning and Acoustic Feature Adaptation in Large-Margin Hidden Markov Models. IEEE J. Sel. Top. Signal Process. 4 (6) (2010)
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, Fernando Pereira
Exploiting Feature Covariance in High-Dimensional Online Learning. AISTATS (2010)
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
Matrix updates for perceptron training of continuous density hidden Markov models. ICML (2009)
Diane Hu, Lawrence K. Saul
A Probabilistic Topic Model for Unsupervised Learning of Musical Key-Profiles. ISMIR (2009)
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Identifying suspicious URLs: an application of large-scale online learning. ICML (2009)
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
Large-margin feature adaptation for automatic speech recognition. ASRU (2009)
Kilian Q. Weinberger, Lawrence K. Saul
Distance Metric Learning for Large Margin Nearest Neighbor Classification. J. Mach. Learn. Res. 10 (2009)
Youngmin Cho, Lawrence K. Saul
Learning dictionaries of stable autoregressive models for audio scene analysis. ICML (2009)
Youngmin Cho, Lawrence K. Saul
Sparse decomposition of mixed audio signals by basis pursuit with autoregressive models. ICASSP (2009)
Youngmin Cho, Lawrence K. Saul
Kernel Methods for Deep Learning. NIPS (2009)
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Beyond blacklists: learning to detect malicious web sites from suspicious URLs. KDD (2009)
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
A fast online algorithm for large margin training of continuous density hidden Markov models. INTERSPEECH (2009)
Stuart J. Russell, Lawrence K. Saul
Technical perspective - The ultimate pilot program. Commun. ACM 52 (7) (2009)
Kilian Q. Weinberger, Lawrence K. Saul
Fast solvers and efficient implementations for distance metric learning. ICML (2008)
Chih-Chieh Cheng, D. Jingtong Hu, Lawrence K. Saul
Nonnegative matrix factorization for real time musical analysis and sight-reading evaluation. ICASSP (2008)
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinberger, Lawrence K. Saul
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data. ICMLA (2008)
Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee
Multiplicative Updates for Nonnegative Quadratic Programming. Neural Comput. 19 (8) (2007)
Fei Sha, Y. Albert Park, Lawrence K. Saul
-Regularized Linear and Logistic Regression. IDA (2007)
Fei Sha, Lawrence K. Saul
Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models. ICASSP (4) (2007)
Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul
Graph Laplacian Regularization for Large-Scale Semidefinite Programming. NIPS (2006)
Kilian Q. Weinberger, Lawrence K. Saul
An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding. AAAI (2006)
Fei Sha, Lawrence K. Saul
Large Margin Gaussian Mixture Modeling for Phonetic Classification and Recognition. ICASSP (1) (2006)
Fei Sha, Lawrence K. Saul
Large Margin Hidden Markov Models for Automatic Speech Recognition. NIPS (2006)
Kilian Q. Weinberger, Lawrence K. Saul
Unsupervised Learning of Image Manifolds by Semidefinite Programming. Int. J. Comput. Vis. 70 (1) (2006)
Yun Mao, Lawrence K. Saul, Jonathan M. Smith
IDES: An Internet Distance Estimation Service for Large Networks. IEEE J. Sel. Areas Commun. 24 (12) (2006)
John Ashley Burgoyne, Lawrence K. Saul
Visualization of low Dimensional Structure in tonal pitch Space. ICMC (2005)
John Ashley Burgoyne, Lawrence K. Saul
Learning Harmonic Relationships in Digital Audio with Dirichlet-Based Hidden Markov Models. ISMIR (2005)
Fei Sha, Lawrence K. Saul
Analysis and extension of spectral methods for nonlinear dimensionality reduction. ICML (2005)
Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul
Distance Metric Learning for Large Margin Nearest Neighbor Classification. NIPS (2005)
Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul
Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization. AISTATS (2005)
Jihun Ham, Daniel D. Lee, Lawrence K. Saul
Semisupervised alignment of manifolds. AISTATS (2005)
Viren Jain, Lawrence K. Saul
Exploratory analysis and visualization of speech and music by locally linear embedding. ICASSP (3) (2004)
John Blitzer, Kilian Q. Weinberger, Lawrence K. Saul, Fernando Pereira
Hierarchical Distributed Representations for Statistical Language Modeling. NIPS (2004)
Kilian Q. Weinberger, Lawrence K. Saul
Unsupervised Learning of Image Manifolds by Semidefinite Programming. CVPR (2) (2004)
Fei Sha, John Ashley Burgoyne, Lawrence K. Saul
estimation in speech. ICASSP (5) (2004)
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
Learning a kernel matrix for nonlinear dimensionality reduction. ICML (2004)
Fei Sha, Lawrence K. Saul
Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization. NIPS (2004)
Yuanqing Lin, Daniel D. Lee, Lawrence K. Saul
Nonnegative deconvolution for time of arrival estimation. ICASSP (2) (2004)
Yun Mao, Lawrence K. Saul
Modeling distances in large-scale networks by matrix factorization. Internet Measurement Conference (2004)
Lawrence K. Saul, Sam T. Roweis
Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifold. J. Mach. Learn. Res. 4 (2003)
Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar
A Generalized Linear Model for Principal Component Analysis of Binary Data. AISTATS (2003)
Fei Sha, Lawrence K. Saul, Daniel D. Lee
Multiplicative Updates for Large Margin Classifiers. COLT (2003)
Lawrence K. Saul, Fei Sha, Daniel D. Lee
Statistical signal processing with nonnegativity constraints. INTERSPEECH (2003)
Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell Jr., Yann LeCun
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. NIPS (2002)
Fei Sha, Lawrence K. Saul, Daniel D. Lee
Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. NIPS (2002)
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton
Global Coordination of Local Linear Models. NIPS (2001)
Lawrence K. Saul, Mazin G. Rahim, Jont B. Allen
A statistical model for robust integration of narrowband cues in speech. Comput. Speech Lang. 15 (2) (2001)
Mazin G. Rahim, Giuseppe Riccardi, Lawrence K. Saul, Jeremy H. Wright, Bruce Buntschuh, Allen L. Gorin
Robust numeric recognition in spoken language dialogue. Speech Commun. 34 (1-2) (2001)
Lawrence K. Saul, Daniel D. Lee
Multiplicative Updates for Classification by Mixture Models. NIPS (2001)
Lawrence K. Saul, Michael I. Jordan
Attractor Dynamics in Feedforward Neural Networks. Neural Comput. 12 (6) (2000)
Lawrence K. Saul, Jont B. Allen
Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech. NIPS (2000)
Lawrence K. Saul, Mazin G. Rahim
Markov Processes on Curves. Mach. Learn. 41 (3) (2000)
Lawrence K. Saul, Mazin G. Rahim
Maximum likelihood and minimum classification error factor analysis for automatic speech recognition. IEEE Trans. Speech Audio Process. 8 (2) (2000)
Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul
An Introduction to Variational Methods for Graphical Models. Mach. Learn. 37 (2) (1999)
Lawrence K. Saul, Mazin G. Rahim
Modeling the rate of speech by Markov processes on curves. EUROSPEECH (1999)
Lawrence K. Saul, Michael I. Jordan
Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones. Mach. Learn. 37 (1) (1999)

Lawrence K. Saul.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Lawrence K. Saul