Larry A. Wasserman

Orcid: 0000-0001-5461-8760

Affiliations:
  • Carnegie Mellon University, Pittsburgh, USA


According to our database1, Larry A. Wasserman authored at least 88 papers between 1992 and 2023.

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Bibliography

2023
Simultaneous inference for generalized linear models with unmeasured confounders.
CoRR, 2023

2022
Interactive rank testing by betting.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
Universal Inference Meets Random Projections: A Scalable Test for Log-concavity.
CoRR, 2021

Forest Guided Smoothing.
CoRR, 2021

2020
Efficient Topological Layer based on Persistent Landscapes.
CoRR, 2020

PLLay: Efficient Topological Layer based on Persistent Landscapes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Familywise Error Rate Control by Interactive Unmasking.
Proceedings of the 37th International Conference on Machine Learning, 2020

Homotopy Reconstruction via the Cech Complex and the Vietoris-Rips Complex.
Proceedings of the 36th International Symposium on Computational Geometry, 2020

2019
Minimax rates for estimating the dimension of a manifold.
J. Comput. Geom., 2019

Nerve Theorem on a Positive Reach set.
CoRR, 2019

Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Cautious Deep Learning.
CoRR, 2018

2017
Robust Topological Inference: Distance To a Measure and Kernel Distance.
J. Mach. Learn. Res., 2017

Hypothesis Testing for High-Dimensional Multinomials: A Selective Review.
CoRR, 2017

Hypothesis Testing For Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates.
CoRR, 2017

2016
Least Ambiguous Set-Valued Classifiers with Bounded Error Levels.
CoRR, 2016

Classification Accuracy as a Proxy for Two Sample Testing.
CoRR, 2016

Statistical Inference for Cluster Trees.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Minimax lower bounds for linear independence testing.
Proceedings of the IEEE International Symposium on Information Theory, 2016

2015
Stochastic convergence of persistence landscapes and silhouettes.
J. Comput. Geom., 2015

On Clinical Pathway Discovery from Electronic Health Record Data.
IEEE Intell. Syst., 2015

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing.
CoRR, 2015

Risk Bounds For Mode Clustering.
CoRR, 2015

A conformal prediction approach to explore functional data.
Ann. Math. Artif. Intell., 2015

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal Ridge Detection using Coverage Risk.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Statistical View on the Expressive Timing of Piano Rolled Chords.
Proceedings of the 16th International Society for Music Information Retrieval Conference, 2015

Subsampling Methods for Persistent Homology.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

On Estimating L22 Divergence.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Statistical analysis of metric graph reconstruction.
J. Mach. Learn. Res., 2014

Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions.
CoRR, 2014

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives.
CoRR, 2014

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations.
CoRR, 2014

Generalized Mode and Ridge Estimation.
CoRR, 2014

Nonparametric Estimation of Renyi Divergence and Friends.
Proceedings of the 31th International Conference on Machine Learning, 2014

On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease.
Proceedings of the AMIA 2014, 2014

An Analysis of Active Learning with Uniform Feature Noise.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Random Differential Privacy.
J. Priv. Confidentiality, 2013

Differential privacy for functions and functional data.
J. Mach. Learn. Res., 2013

Statistical Inference For Persistent Homology
CoRR, 2013

Estimating Undirected Graphs Under Weak Assumptions.
CoRR, 2013

Nonparametric Inference For Density Modes.
CoRR, 2013

Uncertainty Measures and Limiting Distributions for Filament Estimation.
CoRR, 2013

On the Bootstrap for Persistence Diagrams and Landscapes.
CoRR, 2013

Tight Lower Bounds for Homology Inference.
CoRR, 2013

Cluster Trees on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Distribution-Free Distribution Regression.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Minimaxity, Statistical Thinking and Differential Privacy.
J. Priv. Confidentiality, 2012

The huge Package for High-dimensional Undirected Graph Estimation in R.
J. Mach. Learn. Res., 2012

Stability of density-based clustering.
J. Mach. Learn. Res., 2012

Minimax Manifold Estimation.
J. Mach. Learn. Res., 2012

A Comparison of the Lasso and Marginal Regression.
J. Mach. Learn. Res., 2012

Minimax rates for homology inference.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Nonparametric Ridge Estimation
CoRR, 2012

Density-Sensitive Semisupervised Inference
CoRR, 2012

Distribution Free Prediction Bands
CoRR, 2012

Sparse Nonparametric Graphical Models
CoRR, 2012

The Nonparanormal SKEPTIC.
CoRR, 2012

Exponential Concentration for Mutual Information Estimation with Application to Forests.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

High Dimensional Semiparametric Gaussian Copula Graphical Models.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Forest Density Estimation.
J. Mach. Learn. Res., 2011

Union Support Recovery in Multi-task Learning.
J. Mach. Learn. Res., 2011

Efficient Nonparametric Conformal Prediction Regions
CoRR, 2011

Manifold Estimation and Singular Deconvolution Under Hausdorff Loss
CoRR, 2011

2010
Time varying undirected graphs.
Mach. Learn., 2010

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Graph-Valued Regression.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Forest Density Estimation.
Proceedings of the COLT 2010, 2010

2009
Compressed and Privacy-Sensitive Sparse Regression.
IEEE Trans. Inf. Theory, 2009

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs.
J. Mach. Learn. Res., 2009

Estimating the Error Distribution of a Single Tap Sequence without Ground Truth.
Proceedings of the 10th International Society for Music Information Retrieval Conference, 2009

Differential privacy with compression.
Proceedings of the IEEE International Symposium on Information Theory, 2009

2008
Nonparametric regression and classification with joint sparsity constraints.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Compressed Regression.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

SpAM: Sparse Additive Models.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Statistical Analysis of Semi-Supervised Regression.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005
Rodeo: Sparse Nonparametric Regression in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Active Learning For Identifying Function Threshold Boundaries.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2001
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

1999
Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field.
AI Mag., 1999

A variable-rate filtering system for digital communications.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

1997
Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

1992
Comments on shafer's "perspectives on the theory and practice of belief functions".
Int. J. Approx. Reason., 1992


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