Lawrence K. Saul

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All published works

Action	Title	Year	Authors
+ PDF Chat	EigenVI: score-based variational inference with orthogonal function expansions	2024	Diana Cai Chirag Modi Charles C. Margossian R. Michael Gower David M. Blei Lawrence K. Saul
+ PDF Chat	Batch, match, and patch: low-rank approximations for score-based variational inference	2024	Chirag Modi Diana Cai Lawrence K. Saul
+ PDF Chat	Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix	2024	Charles C. Margossian Lawrence K. Saul
+ PDF Chat	An Ordering of Divergences for Variational Inference with Factorized Gaussian Approximations	2024	Charles C. Margossian Loucas Pillaud-Vivien Lawrence K. Saul
+ PDF Chat	Batch and match: black-box variational inference with a score-based divergence	2024	Diana Cai Chirag Modi Loucas Pillaud-Vivien Charles C. Margossian Robert M. Gower David M. Blei Lawrence K. Saul
+	The Shrinkage-Delinkage Trade-off: An Analysis of Factorized Gaussian Approximations for Variational Inference	2023	Charles C. Margossian Lawrence K. Saul
+	Variational Inference with Gaussian Score Matching	2023	Chirag Modi Charles C. Margossian Yuling Yao Robert M. Gower David M. Blei Lawrence K. Saul
+	Generating correctness proofs with neural networks	2020	Alex Sanchez-Stern Yousef Alhessi Lawrence K. Saul Sorin Lerner
+	Generating Correctness Proofs with Neural Networks	2019	Alex Sanchez-Stern Yousef Alhessi Lawrence K. Saul Sorin Lerner
+	Generating Correctness Proofs with Neural Networks	2019	Alex Sanchez-Stern Yousef Alhessi Lawrence K. Saul Sorin Lerner
+	Large Deviation Methods for Approximate Probabilistic Inference	2013	Michael Kearns Lawrence K. Saul
+	Large Deviation Methods for Approximate Probabilistic Inference	2013	Michael Kearns Lawrence K. Saul
+	Nonnegative Matrix Factorization for Semi-supervised Dimensionality Reduction	2011	Youngmin Cho Lawrence K. Saul
+	Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification	2011	Youngmin Cho Lawrence K. Saul
+	Graph Laplacian Regularization for Large-Scale Semidefinite Programming	2007	Kilian Q. Weinberger Fei Sha Qihui Zhu Lawrence K. Saul
+ PDF Chat	Multiplicative Updates for Nonnegative Quadratic Programming	2007	Fei Sha Yuanqing Lin Lawrence K. Saul Daniel D. Lee
+ PDF Chat	Multiplicative Updates for L 1–Regularized Linear and Logistic Regression	2007	Fei Sha Youngjun Park Lawrence K. Saul
+	Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines	2002	Fei Sha Lawrence K. Saul Daniel D. Lee
+ PDF Chat	None	1999	Lawrence K. Saul Michael I. Jordan
+	Inference in Multilayer Networks via Large Deviation Bounds	1998	Michael Kearns Lawrence K. Saul
+	Aggregate and mixed-order Markov models for statistical language processing	1997	Lawrence K. Saul Fernando Pereira
+	Aggregate and mixed-order Markov models for statistical language processing	1997	Lawrence K. Saul Fernando Pereira
+	Learning in Boltzmann Trees	1994	Lawrence K. Saul Michael I. Jordan
+	Exact computations in the statistical mechanics of disordered systems	1994	Lawrence K. Saul
+	Boltzmann Chains and Hidden Markov Models	1994	Lawrence K. Saul Michael I. Jordan

Common Coauthors

Coauthor	Papers Together
Charles C. Margossian	6
Fei Sha	4
Chirag Modi	4
David M. Blei	3
Alex Sanchez-Stern	3
Yousef Alhessi	3
Michael Kearns	3
Sorin Lerner	3
Michael I. Jordan	3
Diana Cai	3
Robert M. Gower	2
Fernando Pereira	2
Youngmin Cho	2
Loucas Pillaud-Vivien	2
Daniel D. Lee	2
Yuanqing Lin	1
Qihui Zhu	1
R. Michael Gower	1
Yuling Yao	1
Youngjun Park	1
Kilian Q. Weinberger	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	6
+	An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process	1972	Leonard E. Baum	3
+	An Empirical Study of Smoothing Techniques for Language Modeling	1996	Stanley F. Chen Joshua Goodman	3
+ PDF Chat	ACL2(ml): Machine-Learning for ACL2	2014	Jónathan Heras Ekaterina Komendantskaya	2
+	Learning to Prove Theorems via Interacting with Proof Assistants	2019	Kaiyu Yang Jia Deng	2
+	Primal-Dual Interior-Point Methods	1997	Stephen J. Wright	2
+	A deep language model for software code	2016	Hoa Khanh Dam Truyen Tran Trang Pham	2
+	Deep Network Guided Proof Search	2017	Sarah M. Loos Geoffrey Irving Christian Szegedy Cezary Kaliszyk	2
+	HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving	2017	Cezary Kaliszyk François Chollet Christian Szegedy	2
+	Statistical Field Theory	1989	C. Itzykson Jean-Michel Drouffe	2
+	Towards Proof Synthesis Guided by Neural Machine Translation for Intuitionistic Propositional Logic	2017	Taro Sekiyama Akifumi Imanishi Kohei Suenaga	2
+ PDF Chat	Combined reconstruction of weak and strong lensing data with WSLAP	2007	J. M. Diego Max Tegmark Pavlos Protopapas H. B. Sandvik	2
+	A Survey of Machine Learning for Big Code and Naturalness	2017	Miltiadis Allamanis Earl T. Barr Prémkumar Dévanbu Charles Sutton	2
+	GamePad: A Learning Environment for Theorem Proving	2018	Daniel Huang Prafulla Dhariwal Dawn Song Ilya Sutskever	2
+ PDF Chat	Generalized Iterative Scaling for Log-Linear Models	1972	J. N. Darroch D. Ratcliff	2
+	A Learning Algorithm for Boltzmann Machines*	1985	David H. Ackley Geoffrey E. Hinton Terrence J. Sejnowski	2
+	Graph Representations for Higher-Order Logic and Theorem Proving	2019	Aditya Paliwal Sarah M. Loos Markus N. Rabe Kshitij Bansal Christian Szegedy	2
+	Aggregate and mixed-order Markov models for statistical language processing	1997	Lawrence K. Saul Fernando Pereira	1
+ PDF Chat	$I$-Divergence Geometry of Probability Distributions and Minimization Problems	1975	Imre Csiszár	1
+	An Interior-Point Method for Large-Scale '1-Regularized Logistic Regression	2007	Kwangmoo Koh Seung-Jean Kim Stephen Boyd	1
+	Learning in Boltzmann Trees	1994	Lawrence K. Saul Michael I. Jordan	1
+ PDF Chat	Convolutional Neural Networks over Tree Structures for Programming Language Processing	2016	Lili Mou Ge Li Lu Zhang Tao Wang Zhi Jin	1
+	Convex Optimization	2004	Stephen Boyd Lieven Vandenberghe	1
+	DeepMath - Deep Sequence Models for Premise Selection	2016	Alex Alemi François Chollet Niklas Eén Geoffrey Irving Christian Szegedy Josef Urban	1
+	Nonlinear Programming	1995	Dimitri P. Bertsekas	1
+	Semidefinite Programming	1996	Lieven Vandenberghe Stephen Boyd	1
+	HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version)	2019	Kshitij Bansal Sarah M. Loos Markus N. Rabe Christian Szegedy Stewart Wilcox	1
+	Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	1
+	HOList: An Environment for Machine Learning of Higher-Order Theorem Proving	2019	Kshitij Bansal Sarah M. Loos Markus N. Rabe Christian Szegedy Stewart Wilcox	1
+	Aggregate and mixed-order Markov models for statistical language processing	1997	Lawrence K. Saul Fernando Pereira	1
+	Natural Deduction as Higher-Order Resolution	1993	Lawrence C. Paulson	1
+	Supervised Dictionary Learning	2008	Julien Mairal Francis Bach Jean Ponce Guillermo Sapiro Andrew Zisserman	1
+	Update Rules for Parameter Estimation in Bayesian Networks	2013	Eric Bauer Daphne Koller Yoram Singer	1
+ PDF Chat	EAZY: A Fast, Public Photometric Redshift Code	2008	Gabriel Brammer Pieter van Dokkum P. Coppi	1
+ PDF Chat	TacticToe: Learning to Reason with HOL4 Tactics	2018	Thibault Gauthier Cezary Kaliszyk Josef Urban	1
+	None	2000	Tommi Jaakkola Michael I. Jordan	1
+	Convex Optimization	2004	Stephen Boyd Lieven Vandenberghe	1
+	TBCNN: A Tree-Based Convolutional Neural Network for Programming Language Processing.	2014	Lili Mou Ge Li Zhi Jin Lu Zhang Tao Wang	1
+	Spectral Graph Theory	1996	Fan Chung	1
+ PDF Chat	Machine Learning in Proof General: Interfacing Interfaces	2013	Ekaterina Komendantskaya Jónathan Heras Gudmund Grov	1
+	CSDP, A C library for semidefinite programming	1999	Brian Borchers	1
+ PDF Chat	Multiplicative Updates for Nonnegative Quadratic Programming	2007	Fei Sha Yuanqing Lin Lawrence K. Saul Daniel D. Lee	1
+	An Interior-Point Method for Large-Scale l 1 -Regularized Logistic Regression	2007	Kwangmoo Koh Seung-Jean Kim Stephen Boyd	1
+	Gradient projection methods for quadratic programs and applications in training support vector machines	2005	Thomas Serafini Gaetano Zanghirati Luca Zanni	1
+	Nonlinear Programming: A Unified Approach	1972	David W. Peterson Willard I. Zangwill	1
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	1
+ PDF Chat	The two-dimensional Ising model	2018	Barry M. McCoy Tai Tsun Wu	1
+ PDF Chat	The Fastest Mixing Markov Process on a Graph and a Connection to a Maximum Variance Unfolding Problem	2006	Jun Sun Stephen Boyd Lin Xiao Persi Diaconis	1
+	Supervised Dictionary Learning	2008	Julien Mairal Jean Ponce Guillermo Sapiro Andrew Zisserman Francis R. Bach	1
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	1