Larry A. Wasserman

115 papers A* 12A 9B 2Misc 2Journal 73Unranked 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Disentangled Feature Importance. CoRR Jin-Hong Du, Kathryn Roeder, Larry A. Wasserman
2025	J	`jnl`	Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives. CoRR Sivaraman Balakrishnan, Tudor Manole, Larry A. Wasserman
2025	J	`jnl`	Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity. J. Comput. Graph. Stat. Robin Dunn, Aditya Gangrade, Larry A. Wasserman, Aaditya Ramdas
2024	J	`jnl`	Assumption-Lean Post-Integrated Inference with Negative Control Outcomes. CoRR Jin-Hong Du, Kathryn Roeder, Larry A. Wasserman
2024	J	`jnl`	Decorrelated Variable Importance. J. Mach. Learn. Res. Isabella Verdinelli, Larry A. Wasserman
2024	A*	`conf`	Hierarchical and Density-based Causal Clustering. NeurIPS Kwangho Kim, Jisu Kim, Larry A. Wasserman, Edward H. Kennedy
2024	J	`jnl`	Hierarchical and Density-based Causal Clustering. CoRR Kwangho Kim, Jisu Kim, Larry A. Wasserman, Edward H. Kennedy
2023	J	`jnl`	Simultaneous inference for generalized linear models with unmeasured confounders. CoRR Jin-Hong Du, Larry A. Wasserman, Kathryn Roeder
2022	—	`conf`	Interactive rank testing by betting. CLeaR Boyan Duan, Aaditya Ramdas, Larry A. Wasserman
2021	J	`jnl`	Forest Guided Smoothing. CoRR Isabella Verdinelli, Larry A. Wasserman
2021	J	`jnl`	Universal Inference Meets Random Projections: A Scalable Test for Log-concavity. CoRR Robin Dunn, Larry A. Wasserman, Aaditya Ramdas
2020	J	`jnl`	Efficient Topological Layer based on Persistent Landscapes. CoRR Kwangho Kim, Jisu Kim, Joon Sik Kim, Frédéric Chazal, Larry A. Wasserman
2020	A*	`conf`	Familywise Error Rate Control by Interactive Unmasking. ICML Boyan Duan, Aaditya Ramdas, Larry A. Wasserman
2020	A*	`conf`	Homotopy Reconstruction via the Cech Complex and the Vietoris-Rips Complex. SoCG Jisu Kim, Jaehyeok Shin, Frédéric Chazal, Alessandro Rinaldo, Larry A. Wasserman
2020	A*	`conf`	PLLay: Efficient Topological Layer based on Persistent Landscapes. NeurIPS Kwangho Kim, Jisu Kim, Manzil Zaheer, Joon Sik Kim, Frédéric Chazal, Larry A. Wasserman
2020	J	`jnl`	The huge Package for High-dimensional Undirected Graph Estimation in R. CoRR Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry A. Wasserman
2019	J	`jnl`	Minimax rates for estimating the dimension of a manifold. J. Comput. Geom. Jisu Kim, Alessandro Rinaldo, Larry A. Wasserman
2019	J	`jnl`	Nerve Theorem on a Positive Reach set. CoRR Jisu Kim, Jaehyeok Shin, Alessandro Rinaldo, Larry A. Wasserman
2019	A*	`conf`	Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension. ICML Jisu Kim, Jaehyeok Shin, Alessandro Rinaldo, Larry A. Wasserman
2018	J	`jnl`	Cautious Deep Learning. CoRR Yotam Hechtlinger, Barnabás Póczos, Larry A. Wasserman
2017	J	`jnl`	Hypothesis Testing For Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates. CoRR Sivaraman Balakrishnan, Larry A. Wasserman
2017	J	`jnl`	Hypothesis Testing for High-Dimensional Multinomials: A Selective Review. CoRR Sivaraman Balakrishnan, Larry A. Wasserman
2017	J	`jnl`	Robust Topological Inference: Distance To a Measure and Kernel Distance. J. Mach. Learn. Res. Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry A. Wasserman
2016	J	`jnl`	Classification Accuracy as a Proxy for Two Sample Testing. CoRR Aaditya Ramdas, Aarti Singh, Larry A. Wasserman
2016	J	`jnl`	Least Ambiguous Set-Valued Classifiers with Bounded Error Levels. CoRR Mauricio Sadinle, Jing Lei, Larry A. Wasserman
2016	J	`jnl`	Minimax Lower Bounds for Linear Independence Testing. CoRR Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	J	`jnl`	Minimax Rates for Estimating the Dimension of a Manifold. CoRR Jisu Kim, Alessandro Rinaldo, Larry A. Wasserman
2016	B	`conf`	Minimax lower bounds for linear independence testing. ISIT Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	—	`conf`	Statistical Inference for Cluster Trees. NIPS Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry A. Wasserman
2015	—	`conf`	A Statistical View on the Expressive Timing of Piano Rolled Chords. ISMIR Mutian Fu, Guangyu Xia, Roger B. Dannenberg, Larry A. Wasserman
2015	J	`jnl`	A conformal prediction approach to explore functional data. Ann. Math. Artif. Intell. Jing Lei, Alessandro Rinaldo, Larry A. Wasserman
2015	J	`jnl`	Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	An Analysis of Active Learning With Uniform Feature Noise. CoRR Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	A	`conf`	Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. AISTATS Martin Azizyan, Aarti Singh, Larry A. Wasserman
2015	—	`conf`	Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations. NIPS Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins
2015	J	`jnl`	On Clinical Pathway Discovery from Electronic Health Record Data. IEEE Intell. Syst. Yiye Zhang, Rema Padman, Larry A. Wasserman, Nirav Patel, Pradip Teredesai, Qizhi Xie
2015	A	`conf`	On Estimating L22 Divergence. AISTATS Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman
2015	A*	`conf`	On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. AAAI Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	A	`conf`	On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. AISTATS Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	—	`conf`	Optimal Ridge Detection using Coverage Risk. NIPS Yen-Chi Chen, Christopher R. Genovese, Shirley Ho, Larry A. Wasserman
2015	J	`jnl`	Risk Bounds For Mode Clustering. CoRR Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Stochastic convergence of persistence landscapes and silhouettes. J. Comput. Geom. Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry A. Wasserman
2015	A*	`conf`	Subsampling Methods for Persistent Homology. ICML Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry A. Wasserman
2014	A	`conf`	An Analysis of Active Learning with Uniform Feature Noise. AISTATS Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	Generalized Mode and Ridge Estimation. CoRR Yen-Chi Chen, Christopher R. Genovese, Larry A. Wasserman
2014	J	`jnl`	Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations. CoRR Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins
2014	J	`jnl`	Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. CoRR Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	A*	`conf`	Nonparametric Estimation of Renyi Divergence and Friends. ICML Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman
2014	Misc	`conf`	On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease. AMIA Yiye Zhang, Rema Padman, Larry A. Wasserman
2014	J	`jnl`	On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	Robust Topological Inference: Distance To a Measure and Kernel Distance. CoRR Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry A. Wasserman
2014	J	`jnl`	Statistical analysis of metric graph reconstruction. J. Mach. Learn. Res. Fabrizio Lecci, Alessandro Rinaldo, Larry A. Wasserman
2014	A*	`conf`	Stochastic Convergence of Persistence Landscapes and Silhouettes. SoCG Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry A. Wasserman
2014	J	`jnl`	Subsampling Methods for Persistent Homology. CoRR Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry A. Wasserman
2013	J	`jnl`	A Conformal Prediction Approach to Explore Functional Data CoRR Jing Lei, Alessandro Rinaldo, Larry A. Wasserman
2013	—	`conf`	Cluster Trees on Manifolds. NIPS Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Cluster Trees on Manifolds. CoRR Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Differential privacy for functions and functional data. J. Mach. Learn. Res. Rob Hall, Alessandro Rinaldo, Larry A. Wasserman
2013	J	`jnl`	Distribution-Free Distribution Regression CoRR Barnabás Póczos, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	A	`conf`	Distribution-Free Distribution Regression. AISTATS Barnabás Póczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman
2013	J	`jnl`	Estimating Undirected Graphs Under Weak Assumptions. CoRR Larry A. Wasserman, Mladen Kolar, Alessandro Rinaldo
2013	J	`jnl`	Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk CoRR John D. Lafferty, Larry A. Wasserman
2013	—	`conf`	Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. NIPS Martin Azizyan, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. CoRR Martin Azizyan, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Nonparametric Inference For Density Modes. CoRR Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
2013	J	`jnl`	On the Bootstrap for Persistence Diagrams and Landscapes. CoRR Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Random Differential Privacy. J. Priv. Confidentiality Robert J. Hall, Larry A. Wasserman, Alessandro Rinaldo
2013	J	`jnl`	Statistical Analysis of Metric Graph Reconstruction CoRR Fabrizio Lecci, Alessandro Rinaldo, Larry A. Wasserman
2013	J	`jnl`	Statistical Inference For Persistent Homology CoRR Sivaraman Balakrishnan, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Stochastic Convergence of Persistence Landscapes and Silhouettes. CoRR Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry A. Wasserman
2013	J	`jnl`	Tight Lower Bounds for Homology Inference. CoRR Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Uncertainty Measures and Limiting Distributions for Filament Estimation. CoRR Yen-Chi Chen, Christopher R. Genovese, Larry A. Wasserman
2012	J	`jnl`	A Comparison of the Lasso and Marginal Regression. J. Mach. Learn. Res. Christopher R. Genovese, Jiashun Jin, Larry A. Wasserman, Zhigang Yao
2012	J	`jnl`	Density-Sensitive Semisupervised Inference CoRR Martin Azizyan, Aarti Singh, Larry A. Wasserman
2012	J	`jnl`	Differential Privacy for Functions and Functional Data CoRR Rob Hall, Alessandro Rinaldo, Larry A. Wasserman
2012	J	`jnl`	Distribution Free Prediction Bands CoRR Jing Lei, Larry A. Wasserman
2012	—	`conf`	Exponential Concentration for Mutual Information Estimation with Application to Forests. NIPS Han Liu, John D. Lafferty, Larry A. Wasserman
2012	A*	`conf`	High Dimensional Semiparametric Gaussian Copula Graphical Models. ICML Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012	J	`jnl`	Minimax Manifold Estimation. J. Mach. Learn. Res. Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
2012	A	`conf`	Minimax rates for homology inference. AISTATS Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman
2012	J	`jnl`	Minimaxity, Statistical Thinking and Differential Privacy. J. Priv. Confidentiality Larry A. Wasserman
2012	J	`jnl`	Nonparametric Ridge Estimation CoRR Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
2012	J	`jnl`	Sparse Nonparametric Graphical Models CoRR John D. Lafferty, Han Liu, Larry A. Wasserman
2012	J	`jnl`	Stability of density-based clustering. J. Mach. Learn. Res. Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry A. Wasserman
2012	J	`jnl`	The Nonparanormal SKEPTIC. CoRR Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012	J	`jnl`	The huge Package for High-dimensional Undirected Graph Estimation in R. J. Mach. Learn. Res. Tuo Zhao, Han Liu, Kathryn Roeder, John D. Lafferty, Larry A. Wasserman
2011	J	`jnl`	Efficient Nonparametric Conformal Prediction Regions CoRR Jing Lei, James M. Robins, Larry A. Wasserman
2011	J	`jnl`	Forest Density Estimation. J. Mach. Learn. Res. Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John D. Lafferty, Larry A. Wasserman
2011	J	`jnl`	Manifold Estimation and Singular Deconvolution Under Hausdorff Loss CoRR Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
2011	J	`jnl`	Minimax Rates for Homology Inference CoRR Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman
2011	J	`jnl`	Random Differential Privacy CoRR Rob Hall, Alessandro Rinaldo, Larry A. Wasserman
2011	J	`jnl`	Union Support Recovery in Multi-task Learning. J. Mach. Learn. Res. Mladen Kolar, John D. Lafferty, Larry A. Wasserman
2010	A*	`conf`	Forest Density Estimation. COLT Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu
2010	—	`conf`	Graph-Valued Regression. NIPS Han Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman
2010	J	`jnl`	Minimax Manifold Estimation CoRR Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
2010	—	`conf`	Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models. NIPS Han Liu, Kathryn Roeder, Larry A. Wasserman
2010	J	`jnl`	Time varying undirected graphs. Mach. Learn. Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2009	J	`jnl`	Compressed and Privacy-Sensitive Sparse Regression. IEEE Trans. Inf. Theory Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2009	B	`conf`	Differential privacy with compression. ISIT Shuheng Zhou, Katrina Ligett, Larry A. Wasserman
2009	—	`conf`	Estimating the Error Distribution of a Single Tap Sequence without Ground Truth. ISMIR Roger B. Dannenberg, Larry A. Wasserman
2009	J	`jnl`	The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. J. Mach. Learn. Res. Han Liu, John D. Lafferty, Larry A. Wasserman
2008	—	`conf`	Nonparametric regression and classification with joint sparsity constraints. NIPS Han Liu, John D. Lafferty, Larry A. Wasserman
2008	A*	`conf`	Time Varying Undirected Graphs. COLT Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	J	`jnl`	Compressed Regression CoRR Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	—	`conf`	Compressed Regression. NIPS Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	—	`conf`	SpAM: Sparse Additive Models. NIPS Pradeep Ravikumar, Han Liu, John D. Lafferty, Larry A. Wasserman
2007	A	`conf`	Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo. AISTATS Han Liu, John D. Lafferty, Larry A. Wasserman
2007	—	`conf`	Statistical Analysis of Semi-Supervised Regression. NIPS John D. Lafferty, Larry A. Wasserman
2005	—	`conf`	Active Learning For Identifying Function Threshold Boundaries. NIPS Brent Bryan, Jeff G. Schneider, Robert Nichol, Christopher J. Miller, Christopher R. Genovese, Larry A. Wasserman
2005	—	`conf`	Rodeo: Sparse Nonparametric Regression in High Dimensions. NIPS John D. Lafferty, Larry A. Wasserman
2001	A	`conf`	Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk. UAI John D. Lafferty, Larry A. Wasserman
1999	Misc	`conf`	A variable-rate filtering system for digital communications. ICASSP Larry A. Wasserman, Alan N. Willson Jr.
1999	J	`jnl`	Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field. AI Mag. Sebastian Thrun, Christos Faloutsos, Tom M. Mitchell, Larry A. Wasserman
1997	A	`conf`	Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs. UAI James M. Robins, Larry A. Wasserman
1992	J	`jnl`	Comments on shafer's "perspectives on the theory and practice of belief functions". Int. J. Approx. Reason. Larry A. Wasserman