Comments on shafer's "perspectives on the theory and practice of belief functions". - Larry A. Wasserman (Int. J. Approx. Reason., 1992)

Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs. - James M. Robins; Larry A. Wasserman (UAI, 1997)

A variable-rate filtering system for digital communications. - Larry A. Wasserman; Alan N. Willson Jr. (ICASSP, 1999)

Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field. - Sebastian Thrun; Christos Faloutsos; Tom M. Mitchell; Larry A. Wasserman (AI Mag., 1999)

Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk. - John D. Lafferty; Larry A. Wasserman (UAI, 2001)

Active Learning For Identifying Function Threshold Boundaries. - Brent Bryan; Jeff G. Schneider; Robert Nichol; Christopher J. Miller; Christopher R. Genovese; Larry A. Wasserman (NIPS, 2005)

Rodeo: Sparse Nonparametric Regression in High Dimensions. - John D. Lafferty; Larry A. Wasserman (NIPS, 2005)

Statistical Analysis of Semi-Supervised Regression. - John D. Lafferty; Larry A. Wasserman (NIPS, 2007)

SpAM: Sparse Additive Models. - Pradeep Ravikumar; Han Liu 001; John D. Lafferty; Larry A. Wasserman (NIPS, 2007)

Compressed Regression. - Shuheng Zhou 002; John D. Lafferty; Larry A. Wasserman (NIPS, 2007)

Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo. - Han Liu 001; John D. Lafferty; Larry A. Wasserman (AISTATS, 2007)

Nonparametric regression and classification with joint sparsity constraints. - Han Liu 001; John D. Lafferty; Larry A. Wasserman (NIPS, 2008)

Differential privacy with compression. - Shuheng Zhou 002; Katrina Ligett; Larry A. Wasserman (ISIT, 2009)

Estimating the Error Distribution of a Single Tap Sequence without Ground Truth. - Roger B. Dannenberg; Larry A. Wasserman (ISMIR, 2009)

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. - Han Liu 001; John D. Lafferty; Larry A. Wasserman (J. Mach. Learn. Res., 2009)

Compressed and Privacy-Sensitive Sparse Regression. - Shuheng Zhou 002; John D. Lafferty; Larry A. Wasserman (IEEE Trans. Inf. Theory, 2009)

Forest Density Estimation. - Anupam Gupta 001; John D. Lafferty; Han Liu 001; Larry A. Wasserman; Min Xu 010 (COLT, 2010)

Graph-Valued Regression. - Han Liu 001; Xi Chen 010; John D. Lafferty; Larry A. Wasserman (NIPS, 2010)

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models. - Han Liu 001; Kathryn Roeder; Larry A. Wasserman (NIPS, 2010)

Time varying undirected graphs. - Shuheng Zhou 002; John D. Lafferty; Larry A. Wasserman (Mach. Learn., 2010)

Manifold Estimation and Singular Deconvolution Under Hausdorff Loss - Christopher R. Genovese; Marco Perone-Pacifico; Isabella Verdinelli; Larry A. Wasserman (CoRR, 2011)

Efficient Nonparametric Conformal Prediction Regions - Jing Lei 003; James M. Robins; Larry A. Wasserman (CoRR, 2011)

Union Support Recovery in Multi-task Learning. - Mladen Kolar; John D. Lafferty; Larry A. Wasserman (J. Mach. Learn. Res., 2011)

Forest Density Estimation. - Han Liu 001; Min Xu 010; Haijie Gu; Anupam Gupta 001; John D. Lafferty; Larry A. Wasserman (J. Mach. Learn. Res., 2011)

High Dimensional Semiparametric Gaussian Copula Graphical Models. - Han Liu 001; Fang Han; Ming Yuan 001; John D. Lafferty; Larry A. Wasserman (ICML, 2012)

Exponential Concentration for Mutual Information Estimation with Application to Forests. - Han Liu 001; John D. Lafferty; Larry A. Wasserman (NIPS, 2012)

The Nonparanormal SKEPTIC. - Han Liu 001; Fang Han; Ming Yuan 001; John D. Lafferty; Larry A. Wasserman (CoRR, 2012)

Sparse Nonparametric Graphical Models - John D. Lafferty; Han Liu 001; Larry A. Wasserman (CoRR, 2012)

Distribution Free Prediction Bands - Jing Lei 003; Larry A. Wasserman (CoRR, 2012)

Density-Sensitive Semisupervised Inference - Martin Azizyan; Aarti Singh; Larry A. Wasserman (CoRR, 2012)

Nonparametric Ridge Estimation - Christopher R. Genovese; Marco Perone-Pacifico; Isabella Verdinelli; Larry A. Wasserman (CoRR, 2012)

Minimax rates for homology inference. - Sivaraman Balakrishnan; Alessandro Rinaldo; Don Sheehy; Aarti Singh; Larry A. Wasserman (AISTATS, 2012)

A Comparison of the Lasso and Marginal Regression. - Christopher R. Genovese; Jiashun Jin; Larry A. Wasserman; Zhigang Yao (J. Mach. Learn. Res., 2012)

Minimax Manifold Estimation. - Christopher R. Genovese; Marco Perone-Pacifico; Isabella Verdinelli; Larry A. Wasserman (J. Mach. Learn. Res., 2012)

Stability of density-based clustering. - Alessandro Rinaldo; Aarti Singh; Rebecca Nugent; Larry A. Wasserman (J. Mach. Learn. Res., 2012)

The huge Package for High-dimensional Undirected Graph Estimation in R. - Tuo Zhao; Han Liu 001; Kathryn Roeder; John D. Lafferty; Larry A. Wasserman (J. Mach. Learn. Res., 2012)

Minimaxity, Statistical Thinking and Differential Privacy. - Larry A. Wasserman (J. Priv. Confidentiality, 2012)

Distribution-Free Distribution Regression. - Barnabás Póczos; Aarti Singh; Alessandro Rinaldo; Larry A. Wasserman (AISTATS, 2013)

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. - Martin Azizyan; Aarti Singh; Larry A. Wasserman (NIPS, 2013)

Cluster Trees on Manifolds. - Sivaraman Balakrishnan; Srivatsan Narayanan; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (NIPS, 2013)

Tight Lower Bounds for Homology Inference. - Sivaraman Balakrishnan; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

On the Bootstrap for Persistence Diagrams and Landscapes. - Frédéric Chazal; Brittany Terese Fasy; Fabrizio Lecci; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

Uncertainty Measures and Limiting Distributions for Filament Estimation. - Yen-Chi Chen; Christopher R. Genovese; Larry A. Wasserman (CoRR, 2013)

Nonparametric Inference For Density Modes. - Christopher R. Genovese; Marco Perone-Pacifico; Isabella Verdinelli; Larry A. Wasserman (CoRR, 2013)

Estimating Undirected Graphs Under Weak Assumptions. - Larry A. Wasserman; Mladen Kolar; Alessandro Rinaldo (CoRR, 2013)

Statistical Inference For Persistent Homology - Sivaraman Balakrishnan; Brittany Terese Fasy; Fabrizio Lecci; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

Differential privacy for functions and functional data. - Rob Hall 001; Alessandro Rinaldo; Larry A. Wasserman (J. Mach. Learn. Res., 2013)

Random Differential Privacy. - Robert J. Hall 002; Larry A. Wasserman; Alessandro Rinaldo (J. Priv. Confidentiality, 2013)

An Analysis of Active Learning with Uniform Feature Noise. - Aaditya Ramdas; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (AISTATS, 2014)

On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease. - Yiye Zhang; Rema Padman; Larry A. Wasserman (AMIA, 2014)

Nonparametric Estimation of Renyi Divergence and Friends. - Akshay Krishnamurthy; Kirthevasan Kandasamy; Barnabás Póczos; Larry A. Wasserman (ICML, 2014)

Generalized Mode and Ridge Estimation. - Yen-Chi Chen; Christopher R. Genovese; Larry A. Wasserman (CoRR, 2014)

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations. - Kirthevasan Kandasamy; Akshay Krishnamurthy; Barnabás Póczos; Larry A. Wasserman; James M. Robins (CoRR, 2014)

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. - Aaditya Ramdas; Sashank J. Reddi; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2014)

Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. - Sashank J. Reddi; Aaditya Ramdas; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2014)

Statistical analysis of metric graph reconstruction. - Fabrizio Lecci; Alessandro Rinaldo; Larry A. Wasserman (J. Mach. Learn. Res., 2014)

On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. - Aaditya Ramdas; Sashank Jakkam Reddi; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (AAAI, 2015)

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. - Martin Azizyan; Aarti Singh; Larry A. Wasserman (AISTATS, 2015)

On Estimating L22 Divergence. - Akshay Krishnamurthy; Kirthevasan Kandasamy; Barnabás Póczos; Larry A. Wasserman (AISTATS, 2015)

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. - Sashank J. Reddi; Aaditya Ramdas; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (AISTATS, 2015)

Subsampling Methods for Persistent Homology. - Frédéric Chazal; Brittany Terese Fasy; Fabrizio Lecci; Bertrand Michel; Alessandro Rinaldo; Larry A. Wasserman (ICML, 2015)

A Statistical View on the Expressive Timing of Piano Rolled Chords. - Mutian Fu; Guangyu Xia; Roger B. Dannenberg; Larry A. Wasserman (ISMIR, 2015)

Optimal Ridge Detection using Coverage Risk. - Yen-Chi Chen; Christopher R. Genovese; Shirley Ho; Larry A. Wasserman (NIPS, 2015)

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations. - Kirthevasan Kandasamy; Akshay Krishnamurthy; Barnabás Póczos; Larry A. Wasserman; James M. Robins (NIPS, 2015)

A conformal prediction approach to explore functional data. - Jing Lei 003; Alessandro Rinaldo; Larry A. Wasserman (Ann. Math. Artif. Intell., 2015)

Risk Bounds For Mode Clustering. - Martin Azizyan; Yen-Chi Chen; Aarti Singh; Larry A. Wasserman (CoRR, 2015)

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. - Aaditya Ramdas; Sashank J. Reddi; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2015)

On Clinical Pathway Discovery from Electronic Health Record Data. - Yiye Zhang; Rema Padman; Larry A. Wasserman; Nirav Patel; Pradip Teredesai; Qizhi Xie (IEEE Intell. Syst., 2015)

Stochastic convergence of persistence landscapes and silhouettes. - Frédéric Chazal; Brittany Terese Fasy; Fabrizio Lecci; Alessandro Rinaldo; Larry A. Wasserman (J. Comput. Geom., 2015)

Minimax lower bounds for linear independence testing. - Aaditya Ramdas; David Isenberg; Aarti Singh; Larry A. Wasserman (ISIT, 2016)

Statistical Inference for Cluster Trees. - Jisu Kim; Yen-Chi Chen; Sivaraman Balakrishnan; Alessandro Rinaldo; Larry A. Wasserman (NIPS, 2016)

Classification Accuracy as a Proxy for Two Sample Testing. - Aaditya Ramdas; Aarti Singh; Larry A. Wasserman (CoRR, 2016)

Least Ambiguous Set-Valued Classifiers with Bounded Error Levels. - Mauricio Sadinle; Jing Lei 003; Larry A. Wasserman (CoRR, 2016)

Hypothesis Testing For Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates. - Sivaraman Balakrishnan; Larry A. Wasserman (CoRR, 2017)

Hypothesis Testing for High-Dimensional Multinomials: A Selective Review. - Sivaraman Balakrishnan; Larry A. Wasserman (CoRR, 2017)

Robust Topological Inference: Distance To a Measure and Kernel Distance. - Frédéric Chazal; Brittany Terese Fasy; Fabrizio Lecci; Bertrand Michel; Alessandro Rinaldo; Larry A. Wasserman (J. Mach. Learn. Res., 2017)

Cautious Deep Learning. - Yotam Hechtlinger; Barnabás Póczos; Larry A. Wasserman (CoRR, 2018)

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

Nerve Theorem on a Positive Reach set. - Jisu Kim; Jaehyeok Shin; Alessandro Rinaldo; Larry A. Wasserman (CoRR, 2019)

Minimax rates for estimating the dimension of a manifold. - Jisu Kim; Alessandro Rinaldo; Larry A. Wasserman (J. Comput. Geom., 2019)

Homotopy Reconstruction via the Cech Complex and the Vietoris-Rips Complex. - Jisu Kim; Jaehyeok Shin; Frédéric Chazal; Alessandro Rinaldo; Larry A. Wasserman (SoCG, 2020)

Familywise Error Rate Control by Interactive Unmasking. - Boyan Duan; Aaditya Ramdas; Larry A. Wasserman (ICML, 2020)

PLLay: Efficient Topological Layer based on Persistent Landscapes. - Kwangho Kim; Jisu Kim; Manzil Zaheer; Joon Sik Kim; Frédéric Chazal; Larry A. Wasserman (NeurIPS, 2020)

Efficient Topological Layer based on Persistent Landscapes. - Kwangho Kim; Jisu Kim; Joon Sik Kim; Frédéric Chazal; Larry A. Wasserman (CoRR, 2020)

Forest Guided Smoothing. - Isabella Verdinelli; Larry A. Wasserman (CoRR, 2021)

Universal Inference Meets Random Projections: A Scalable Test for Log-concavity. - Robin Dunn; Larry A. Wasserman; Aaditya Ramdas (CoRR, 2021)

Interactive rank testing by betting. - Boyan Duan; Aaditya Ramdas; Larry A. Wasserman (CLeaR, 2022)

Simultaneous inference for generalized linear models with unmeasured confounders. - Jin-Hong Du; Larry A. Wasserman; Kathryn Roeder (CoRR, 2023)

Hierarchical and Density-based Causal Clustering. - Kwangho Kim; Jisu Kim; Larry A. Wasserman; Edward H. Kennedy (NeurIPS, 2024)

Assumption-Lean Post-Integrated Inference with Negative Control Outcomes. - Jin-Hong Du; Kathryn Roeder; Larry A. Wasserman (CoRR, 2024)

Decorrelated Variable Importance. - Isabella Verdinelli; Larry A. Wasserman (J. Mach. Learn. Res., 2024)

Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity. - Robin Dunn; Aditya Gangrade; Larry A. Wasserman; Aaditya Ramdas (J. Comput. Graph. Stat., 2025)

Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives. - Sivaraman Balakrishnan; Tudor Manole; Larry A. Wasserman (CoRR, 2025)

Disentangled Feature Importance. - Jin-Hong Du; Kathryn Roeder; Larry A. Wasserman (CoRR, 2025)