Larry A. Wasserman

发表

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations pdf

James M. Robins, Kirthevasan Kandasamy, Akshay Krishnamurthy, 2014, ArXiv.

Generalized Mode and Ridge Estimation pdf

Larry A. Wasserman, Yen-Chi Chen, Christopher R. Genovese, 2014, ArXiv.

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs

Larry A. Wasserman, John D. Lafferty, Han Liu, 2009, J. Mach. Learn. Res..

Tight Lower Bounds for Homology Inference pdf

Sivaraman Balakrishnan, Larry A. Wasserman, Alessandro Rinaldo, 2013, ArXiv.

An Analysis of Active Learning with Uniform Feature Noise

Barnabás Póczos, Larry A. Wasserman, Aarti Singh, 2014, AISTATS.

Cautious Deep Learning pdf

Barnabás Póczos, Larry A. Wasserman, Yotam Hechtlinger, 2018, ArXiv.

Least Ambiguous Set-Valued Classifiers With Bounded Error Levels

Larry A. Wasserman, Jing Lei, Mauricio Sadinle, 2016, Journal of the American Statistical Association.

Manifold Estimation and Singular Deconvolution Under Hausdorff Loss pdf

Larry A. Wasserman, Christopher R. Genovese, Marco Perone-Pacifico, 2011, ArXiv.

Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs

James M. Robins, Larry A. Wasserman, J. Robins, 1997, UAI.

Exponential Concentration for Mutual Information Estimation with Application to Forests

Larry A. Wasserman, John D. Lafferty, Han Liu, 2012, NIPS.

Statistical Inference For Persistent Homology pdf

Sivaraman Balakrishnan, Larry A. Wasserman, Alessandro Rinaldo, 2013, arXiv.org.

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models

Larry A. Wasserman, Kathryn Roeder, Han Liu, 2010, NIPS.

Sparse Nonparametric Graphical Models pdf

Larry A. Wasserman, John D. Lafferty, Han Liu, 2012, ArXiv.

On the Bootstrap for Persistence Diagrams and Landscapes pdf

Frédéric Chazal, Larry A. Wasserman, Alessandro Rinaldo, 2013, ArXiv.

Efficient Nonparametric Conformal Prediction Regions pdf

James M. Robins, Larry A. Wasserman, Jing Lei, 2011, ArXiv.

Minimax Manifold Estimation

Larry A. Wasserman, Christopher R. Genovese, Marco Perone-Pacifico, 2010, J. Mach. Learn. Res..

Differential privacy for functions and functional data

Larry A. Wasserman, Rob Hall, Alessandro Rinaldo, 2012, J. Mach. Learn. Res..

Hypothesis Testing For Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates pdf

Sivaraman Balakrishnan, Larry A. Wasserman, L. Wasserman, 2017, The Annals of Statistics.

Statistical Inference for Cluster Trees

Sivaraman Balakrishnan, Larry A. Wasserman, Alessandro Rinaldo, 2016, NIPS.

Non‐parametric inference for density modes pdf

Larry A. Wasserman, Christopher R. Genovese, Marco Perone-Pacifico, 2013, ArXiv.

Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field

Christos Faloutsos, Sebastian Thrun, Larry A. Wasserman, 1999, AI Mag..

Optimal Ridge Detection using Coverage Risk

Larry A. Wasserman, Yen-Chi Chen, Christopher R. Genovese, 2015, NIPS.

Homotopy Reconstruction via the Cech Complex and the Vietoris-Rips Complex

Frédéric Chazal, Larry A. Wasserman, Alessandro Rinaldo, 2020, Symposium on Computational Geometry.

Cluster Trees on Manifolds

Sivaraman Balakrishnan, Larry A. Wasserman, Alessandro Rinaldo, 2013, NIPS.

Minimax lower bounds for linear independence testing

Larry A. Wasserman, Aarti Singh, Aaditya Ramdas, 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

Statistical analysis of metric graph reconstruction

Larry A. Wasserman, Alessandro Rinaldo, Fabrizio Lecci, 2013, J. Mach. Learn. Res..

Robust Topological Inference: Distance To a Measure and Kernel Distance

Frédéric Chazal, Larry A. Wasserman, Alessandro Rinaldo, 2014, J. Mach. Learn. Res..

A conformal prediction approach to explore functional data

Larry A. Wasserman, Alessandro Rinaldo, Jing Lei, 2013, Annals of Mathematics and Artificial Intelligence.

Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo

Larry A. Wasserman, John D. Lafferty, Han Liu, 2007, AISTATS.

Minimax Rates for Estimating the Dimension of a Manifold pdf

Larry A. Wasserman, Alessandro Rinaldo, Jisu Kim, 2016, J. Comput. Geom..

Hypothesis Testing for High-Dimensional Multinomials: A Selective Review pdf

Sivaraman Balakrishnan, Larry A. Wasserman, 2017, ArXiv.

Stability of density-based clustering

Rebecca Nugent, Larry A. Wasserman, Alessandro Rinaldo, 2010, J. Mach. Learn. Res..

Statistical Analysis of Semi-Supervised Regression

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2007, NIPS.

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures

Larry A. Wasserman, Aarti Singh, Martin Azizyan, 2014, AISTATS.

Nerve Theorem on a Positive Reach set pdf

Larry A. Wasserman, Alessandro Rinaldo, Jaehyeok Shin, 2019, ArXiv.

Nonparametric Estimation of Renyi Divergence and Friends

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2014, ICML.

Nonparametric regression and classification with joint sparsity constraints

Larry A. Wasserman, John D. Lafferty, Han Liu, 2008, NIPS.

Distribution-Free Distribution Regression pdf

Barnabás Póczos, Larry A. Wasserman, Alessandro Rinaldo, 2013, AISTATS.

On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions

Barnabás Póczos, Larry A. Wasserman, Aarti Singh, 2014, AAAI.

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations

James M. Robins, Kirthevasan Kandasamy, Akshay Krishnamurthy, 2015, NIPS.

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing pdf

Barnabás Póczos, Larry A. Wasserman, Aarti Singh, 2015, ArXiv.

Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2001, UAI.

Risk Bounds For Mode Clustering pdf

Larry A. Wasserman, Yen-Chi Chen, Aarti Singh, 2015, ArXiv.

Union Support Recovery in Multi-task Learning

Larry A. Wasserman, John D. Lafferty, Mladen Kolar, 2010, J. Mach. Learn. Res..

On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease

Larry A. Wasserman, Rema Padman, Yiye Zhang, 2014, AMIA.

A Statistical View on the Expressive Timing of Piano Rolled Chords

Larry A. Wasserman, Roger B. Dannenberg, Guangyu Xia, 2015, ISMIR.

Active Learning For Identifying Function Threshold Boundaries

Larry A. Wasserman, Christopher R. Genovese, Jeff G. Schneider, 2005, NIPS.

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation

Larry A. Wasserman, Aarti Singh, Martin Azizyan, 2013, NIPS.

Comments on shafer's "perspectives on the theory and practice of belief functions"

Larry A. Wasserman, 1992, Int. J. Approx. Reason..

The Nonparanormal SKEPTIC pdf

Larry A. Wasserman, John D. Lafferty, Fang Han, 2012, ICML 2012.

Nonparametric Ridge Estimation pdf

Larry A. Wasserman, Christopher R. Genovese, Marco Perone-Pacifico, 2012, ArXiv.

Density-Sensitive Semisupervised Inference pdf

Larry A. Wasserman, Aarti Singh, Martin Azizyan, 2012, ArXiv.

High Dimensional Semiparametric Gaussian Copula Graphical Models.

Larry A. Wasserman, John D. Lafferty, Fang Han, 2012, ICML 2012.

SpAM: Sparse Additive Models

Larry A. Wasserman, Pradeep Ravikumar, John D. Lafferty, 2007, NIPS.

Uncertainty Measures and Limiting Distributions for Filament Estimation pdf

Larry A. Wasserman, Yen-Chi Chen, Christopher R. Genovese, 2013, ArXiv.

A Comparison of the Lasso and Marginal Regression

Larry A. Wasserman, Zhigang Yao, Christopher R. Genovese, 2012, J. Mach. Learn. Res..

Compressed and Privacy-Sensitive Sparse Regression

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2009, IEEE Transactions on Information Theory.

Rodeo: Sparse Nonparametric Regression in High Dimensions

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2005, NIPS.

Classification Accuracy as a Proxy for Two Sample Testing pdf

Larry A. Wasserman, Aarti Singh, Aaditya Ramdas, 2016, The Annals of Statistics.

Distribution Free Prediction Bands pdf

Larry A. Wasserman, Jing Lei, L. Wasserman, 2012, ArXiv.

Differential privacy with compression

Larry A. Wasserman, Katrina Ligett, Shuheng Zhou, 2009, 2009 IEEE International Symposium on Information Theory.

Graph-Valued Regression

Xi Chen, Larry A. Wasserman, John D. Lafferty, 2010, NIPS.

A variable-rate filtering system for digital communications

Larry A. Wasserman, Alan N. Willson, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Compressed Regression

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2007, NIPS.

Discussion of “On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning”

Larry A. Wasserman, Sivaraman Balakrishnan, Edward H. Kennedy, 2020, Statistical Science.

The huge Package for High-dimensional Undirected Graph Estimation in R

Larry A. Wasserman, John D. Lafferty, Tuo Zhao, 2012, J. Mach. Learn. Res..

Estimating the Error Distribution of a Single Tap Sequence without Ground Truth

Larry A. Wasserman, Roger B. Dannenberg, 2009, ISMIR.

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives

Barnabás Póczos, Larry A. Wasserman, Aarti Singh, 2015, AISTATS.

Time varying undirected graphs

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2008, Machine Learning.

Minimax rates for homology inference

Sivaraman Balakrishnan, Larry A. Wasserman, Alessandro Rinaldo, 2011, AISTATS.

On Clinical Pathway Discovery from Electronic Health Record Data

Larry A. Wasserman, Rema Padman, Yiye Zhang, 2015, IEEE Intelligent Systems.

On Estimating L22 Divergence

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2015, AISTATS.

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives pdf

Barnabás Póczos, Larry A. Wasserman, Aarti Singh, 2014, ArXiv.

Subsampling Methods for Persistent Homology

Frédéric Chazal, Larry A. Wasserman, Alessandro Rinaldo, 2014, ICML.

Stochastic Convergence of Persistence Landscapes and Silhouettes pdf

Frédéric Chazal, Larry A. Wasserman, Alessandro Rinaldo, 2013, J. Comput. Geom..

Estimating Undirected Graphs Under Weak Assumptions pdf

Larry A. Wasserman, Alessandro Rinaldo, Mladen Kolar, 2013, ArXiv.

Random Differential Privacy pdf

Larry A. Wasserman, Rob Hall, Alessandro Rinaldo, 2011, J. Priv. Confidentiality.