Jason D. Lee

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All published works

Action	Title	Year	Authors
+ PDF Chat	BitDelta: Your Fine-Tune May Only Be Worth One Bit	2024	James Liu Guangxuan Xiao Kai Li Jason D. Lee Song Han Tri Dao Tianle Cai
+	Provable Offline Preference-Based Reinforcement Learning	2023	Wenhao Zhan Masatoshi Uehara Nathan Kallus Jason D. Lee Wen Sun
+	REST: Retrieval-Based Speculative Decoding	2023	Zhenyu He Zexuan Zhong Tianle Cai Jason D. Lee Di He
+	Exact Post Model Selection Inference for Marginal Screening	2014	Jason D. Lee Jonathan Taylor
+	Exact Post Model Selection Inference for Marginal Screening	2014	Jason D. Lee Jonathan Taylor
+	Using multiple samples to learn mixture models	2013	Jason D. Lee Ran Gilad-Bachrach Rich Caruana
+	On model selection consistency of penalized M-estimators: a geometric theory	2013	Jason D. Lee Yuekai Sun Jonathan Taylor
+	Using Multiple Samples to Learn Mixture Models	2013	Jason D. Lee Ran Gilad-Bachrach Rich Caruana
+	Proximal Newton-type methods for convex optimization	2012	Jason D. Lee Yuekai Sun Michael A. Saunders
+	Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form	2012	Jason D. Lee Yuekai Sun Michael A. Saunders
+	Practical Large-Scale Optimization for Max-norm Regularization	2010	Jason D. Lee Ben Recht Nathan Srebro Joel A. Tropp Ruslan Salakhutdinov

Common Coauthors

Coauthor	Papers Together
Jonathan Taylor	3
Yuekai Sun	3
Ran Gilad-Bachrach	2
Rich Caruana	2
Michael A. Saunders	2
Nathan Srebro	1
Ruslan Salakhutdinov	1
Wenhao Zhan	1
Tianle Cai	1
Tianle Cai	1
Kai Li	1
Wen Sun	1
Di He	1
Zhenyu He	1
Song Han	1
Tri Dao	1
Ben Recht	1
Joel A. Tropp	1
Masatoshi Uehara	1
Guangxuan Xiao	1
Zexuan Zhong	1
Nathan Kallus	1
James Liu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)	2009	Martin J. Wainwright	2
+	False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters	2005	Yoav Benjamini Daniel Yekutieli Don Edwards Juliet Popper Shaffer Ajit C. Tamhane Peter H. Westfall Burt Holland	2
+	A Study of Error Variance Estimation in Lasso Regression	2013	Stephen Reid Robert Tibshirani Jerome H. Friedman	2
+	Ultrahigh dimensional feature selection: beyond the linear model.	2009	Jianqing Fan Richard J. Samworth Yichao Wu	2
+	Nonnegativity constraints in numerical analysis	2009	Donghui Chen Robert J. Plemmons	2
+	Valid post-selection inference	2013	Richard A. Berk Lawrence Brown Andreas Buja Kai Zhang Linda Zhao	2
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	2
+	On model selection consistency of penalized M-estimators: a geometric theory	2013	Jason D. Lee Yuekai Sun Jonathan Taylor	2
+ PDF Chat	Sure independence screening in generalized linear models with NP-dimensionality	2010	Jianqing Fan Rui Song	2
+	A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers	2012	Sahand Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu	2
+	Gradient methods for minimizing composite objective function	2007	Yu. Nesterov	2
+ PDF Chat	Sign-constrained least squares estimation for high-dimensional regression	2013	Nicolai Meinshausen	2
+ PDF Chat	Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization	2013	Martin Slawski Matthias Hein	2
+	On Model Selection Consistency of Lasso	2006	Peng Zhao Bin Yu	2
+ PDF Chat	Sure Independence Screening for Ultrahigh Dimensional Feature Space	2008	Jianqing Fan Jinchi Lv	2
+	On asymptotically optimal confidence regions and tests for high-dimensional models	2014	Sara van de Geer Peter Bühlmann Ya’acov Ritov Ruben Dezeure	2
+ PDF Chat	Can one estimate the conditional distribution of post-model-selection estimators?	2006	Hannes Leeb Benedikt M. Pötscher	2
+ PDF Chat	High-dimensional variable selection	2009	Larry Wasserman Kathryn Roeder	2
+	A generalized proximal point algorithm for certain non-convex minimization problems	1981	Masao Fukushima Hisashi Mine	2
+ PDF Chat	In silico prediction of protein-protein interactions in human macrophages	2014	Oussema Souiai Fatma Z. Guerfali Slimane Ben Miled Christine Brun Alia Benkahla	2
+	Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation	2011	Cho‐Jui Hsieh Inderjit S. Dhillon Pradeep Ravikumar Mátyás A. Sustik	1
+	Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm	2009	Mark Schmidt E. van den Berg Michael P. Friedlander Kevin P. Murphy	1
+ PDF Chat	Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization	2010	Benjamin Recht Maryam Fazel Pablo A. Parrilo	1
+ PDF Chat	Templates for convex cone problems with applications to sparse signal recovery	2011	Stephen R. Becker Emmanuel J. Candès Michael C. Grant	1
+	A comparison of the lasso and marginal regression	2012	Christopher R. Genovese Jiashun Jin Larry Wasserman Zhigang Yao	1
+	Confidence intervals and hypothesis testing for high-dimensional regression	2014	Adel Javanmard Andrea Montanari	1
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	1
+	A scalable trust-region algorithm with application to mixed-norm regression	2010	Dong‐Min Kim Suvrit Sra Inderjit S. Dhillon	1
+ PDF Chat	A quasi-Newton proximal splitting method	2012	Stephen Becker Jalal Fadili	1
+	A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization	2003	Samuel Burer Renato D. C. Monteiro	1
+ PDF Chat	Scaled sparse linear regression	2012	Tao Sun C.-H. Zhang	1
+ PDF Chat	Joint covariate selection and joint subspace selection for multiple classification problems	2009	Guillaume Obozinski Ben Taskar Michael I. Jordan	1
+	Convex Sparse Matrix Factorizations	2008	Francis R. Bach Julien Mairal Jean Ponce	1
+	Convex Optimization	2004	Stephen Boyd Lieven Vandenberghe	1
+	Nonlinear Programming and Variational Inequality Problems	1999	Michael Patriksson	1
+	Nonlinear Programming	1995	Dimitri P. Bertsekas	1
+	Exact inference after model selection via the Lasso	2013	Jason D. Lee Dennis L. Sun Yuekai Sun Jonathan Taylor	1
+	Confidence Intervals for Low-Dimensional Parameters in High-Dimensional Linear Models	2011	Cun‐Hui Zhang Stephanie S. Zhang	1
+	Confidence Intervals and Hypothesis Testing for High-Dimensional Regression	2013	Adel Javanmard Andrea Montanari	1
+	Polynomial Learning of Distribution Families	2010	Mikhail Belkin K. P. Sinha	1
+	High-dimensional Ising model selection using ℓ1-regularized logistic regression	2010	Pradeep Ravikumar Martin J. Wainwright John Lafferty	1
+	Exact post-selection inference, with application to the lasso	2016	Jason D. Lee Dennis L. Sun Yuekai Sun Jonathan Taylor	1
+	Statistics for High-Dimensional Data: Methods, Theory and Applications	2011	Peter Bhlmann Sara van de Geer	1
+ PDF Chat	Projected Newton-type Methods in Machine Learning	2011	Mark Schmidt D. Kim Suvrit Sra	1
+	Confidence Intervals for Low-Dimensional Parameters With High-Dimensional Data	2011	Cun‐Hui Zhang Stephanie S. Zhang	1
+	Summing and Nuclear Norms in Banach Space Theory	1987	G. J. O. Jameson	1
+	Learning mixtures of arbitrary gaussians	2001	Sanjeev Arora Ravi Kannan	1
+ PDF Chat	Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming	1995	Michel X. Goemans David P. Williamson	1
+	Interior Gradient and Proximal Methods for Convex and Conic Optimization	2006	A. Auslender Marc Teboulle	1
+	Fixed point and Bregman iterative methods for matrix rank minimization	2009	Shiqian Ma Donald Goldfarb Lifeng Chen	1