Wasserman, Larry

32 publications

JMLR 2024 Decorrelated Variable Importance Isabella Verdinelli, Larry Wasserman

CLeaR 2022 Interactive Rank Testing by Betting Boyan Duan, Aaditya Ramdas, Larry Wasserman

ICML 2020 Familywise Error Rate Control by Interactive Unmasking Boyan Duan, Aaditya Ramdas, Larry Wasserman

NeurIPS 2020 PLLay: Efficient Topological Layer Based on Persistent Landscapes Kwangho Kim, Jisu Kim, Manzil Zaheer, Joon Kim, Frederic Chazal, Larry Wasserman

ICML 2019 Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension Jisu Kim, Jaehyeok Shin, Alessandro Rinaldo, Larry Wasserman

NeurIPS 2016 Statistical Inference for Cluster Trees Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman

NeurIPS 2015 Nonparametric Von Mises Estimators for Entropies, Divergences and Mutual Informations Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabas Poczos, Larry Wasserman, James M Robins

NeurIPS 2015 Optimal Ridge Detection Using Coverage Risk Yen-Chi Chen, Christopher R Genovese, Shirley Ho, Larry Wasserman

ICML 2015 Subsampling Methods for Persistent Homology Frederic Chazal, Brittany Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry Wasserman

ICML 2014 Nonparametric Estimation of Renyi Divergence and Friends Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman

JMLR 2014 Statistical Analysis of Metric Graph Reconstruction Fabrizio Lecci, Alessandro Rinaldo, Larry Wasserman

NeurIPS 2013 Cluster Trees on Manifolds Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry Wasserman

JMLR 2013 Differential Privacy for Functions and Functional Data Rob Hall, Alessandro Rinaldo, Larry Wasserman

NeurIPS 2013 Minimax Theory for High-Dimensional Gaussian Mixtures with Sparse Mean Separation Martin Azizyan, Aarti Singh, Larry Wasserman

JMLR 2012 A Comparison of the Lasso and Marginal Regression Christopher R. Genovese, Jiashun Jin, Larry Wasserman, Zhigang Yao

NeurIPS 2012 Exponential Concentration for Mutual Information Estimation with Application to Forests Han Liu, Larry Wasserman, John D. Lafferty

JMLR 2012 Minimax Manifold Estimation Christopher Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry Wasserman

AISTATS 2012 Minimax Rates for Homology Inference Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh, Larry Wasserman

JMLR 2012 Stability of Density-Based Clustering Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry Wasserman

MLOSS 2012 The Huge Package for High-Dimensional Undirected Graph Estimation in R Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman

JMLR 2011 Forest Density Estimation Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John Lafferty, Larry Wasserman

JMLR 2011 Union Support Recovery in Multi-Task Learning Mladen Kolar, John Lafferty, Larry Wasserman

NeurIPS 2010 Graph-Valued Regression Han Liu, Xi Chen, Larry Wasserman, John D. Lafferty

NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Han Liu, Kathryn Roeder, Larry Wasserman

JMLR 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs Han Liu, John Lafferty, Larry Wasserman

NeurIPS 2008 Nonparametric Regression and Classification with Joint Sparsity Constraints Han Liu, Larry Wasserman, John D. Lafferty

NeurIPS 2007 Compressed Regression Shuheng Zhou, Larry Wasserman, John D. Lafferty

NeurIPS 2007 SpAM: Sparse Additive Models Han Liu, Larry Wasserman, John D. Lafferty, Pradeep K. Ravikumar

AISTATS 2007 Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo Han Liu, John Lafferty, Larry Wasserman

NeurIPS 2007 Statistical Analysis of Semi-Supervised Regression Larry Wasserman, John D. Lafferty

NeurIPS 2005 Active Learning for Identifying Function Threshold Boundaries Brent Bryan, Robert C. Nichol, Christopher R Genovese, Jeff Schneider, Christopher J. Miller, Larry Wasserman

NeurIPS 2005 Rodeo: Sparse Nonparametric Regression in High Dimensions Larry Wasserman, John D. Lafferty