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Forest Guided Smoothing


Mar 08, 2021
Isabella Verdinelli, Larry Wasserman


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


Jun 26, 2020
Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman

* Published on JMLR in 2012 

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Efficient Topological Layer based on Persistent Landscapes


Feb 07, 2020
Kwangho Kim, Jisu Kim, Joon Sik Kim, Frederic Chazal, Larry Wasserman


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Universal Inference Using the Split Likelihood Ratio Test


Feb 04, 2020
Larry Wasserman, Aaditya Ramdas, Sivaraman Balakrishnan


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Gaussian Mixture Clustering Using Relative Tests of Fit


Oct 07, 2019
Purvasha Chakravarti, Sivaraman Balakrishnan, Larry Wasserman


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Minimax Confidence Intervals for the Sliced Wasserstein Distance


Sep 17, 2019
Tudor Manole, Sivaraman Balakrishnan, Larry Wasserman


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Cautious Deep Learning


May 24, 2018
Yotam Hechtlinger, Barnab谩s P贸czos, Larry Wasserman


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Hypothesis Testing for High-Dimensional Multinomials: A Selective Review


Dec 17, 2017
Sivaraman Balakrishnan, Larry Wasserman

* 19 pages, 6 figures. Written in memory of Stephen E. Fienberg 

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


Jun 30, 2017
Sivaraman Balakrishnan, Larry Wasserman

* 60 pages, 6 figures 

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Statistical Inference using the Morse-Smale Complex


Apr 04, 2017
Yen-Chi Chen, Christopher R. Genovese, Larry Wasserman

* 45 pages, 13 figures. Accepted to Electronic Journal of Statistics 

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Distribution-Free Predictive Inference For Regression


Mar 08, 2017
Jing Lei, Max G'Sell, Alessandro Rinaldo, Ryan J. Tibshirani, Larry Wasserman

* 50 pages, 7 figures, 3 tables 

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Statistical Inference for Cluster Trees


Feb 12, 2017
Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman

* 20 pages, 6 figures, accepted in Neural Information Processing Systems (NIPS) 2016 

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Least Ambiguous Set-Valued Classifiers with Bounded Error Levels


Sep 02, 2016
Mauricio Sadinle, Jing Lei, Larry Wasserman

* 35 pages 

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Finding Singular Features


Jun 01, 2016
Christopher Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry Wasserman


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Nonparametric modal regression


Mar 30, 2016
Yen-Chi Chen, Christopher R. Genovese, Ryan J. Tibshirani, Larry Wasserman

* Annals of Statistics 2016, Vol. 44, No. 2, 489-514 
* Published at http://dx.doi.org/10.1214/15-AOS1373 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Classification Accuracy as a Proxy for Two Sample Testing


Feb 06, 2016
Aaditya Ramdas, Aarti Singh, Larry Wasserman

* 15 pages, 2 figures 

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Minimax Lower Bounds for Linear Independence Testing


Jan 23, 2016
Aaditya Ramdas, David Isenberg, Aarti Singh, Larry Wasserman

* 9 pages 

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A Comprehensive Approach to Mode Clustering


Dec 22, 2015
Yen-Chi Chen, Christopher R. Genovese, Larry Wasserman

* 34 pages, 17 figures. Accepted to the Electronic Journal of Statistics. The original title is "Enhanced Mode Clustering" 

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Statistical Analysis of Persistence Intensity Functions


Oct 08, 2015
Yen-Chi Chen, Daren Wang, Alessandro Rinaldo, Larry Wasserman

* 10 pages, 5 figures 

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


Aug 04, 2015
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos, Aarti Singh, Larry Wasserman

* 35 pages, 4 figures 

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


Jun 19, 2015
Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabas Poczos, Larry Wasserman, James M. Robins


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Optimal Ridge Detection using Coverage Risk


Jun 07, 2015
Yen-Chi Chen, Christopher R. Genovese, Shirley Ho, Larry Wasserman

* 16 pages, 4 figures 

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An Analysis of Active Learning With Uniform Feature Noise


May 15, 2015
Aaditya Ramdas, Barnabas Poczos, Aarti Singh, Larry Wasserman

* 24 pages, 2 figures, published in the proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS), 2014 

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Risk Bounds For Mode Clustering


May 03, 2015
Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry Wasserman


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


Nov 24, 2014
Sashank J. Reddi, Aaditya Ramdas, Barnab谩s P贸czos, Aarti Singh, Larry Wasserman

* 19 pages, 9 figures, published in AAAI-15: The 29th AAAI Conference on Artificial Intelligence (with author order reversed from ArXiv) 

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


Nov 23, 2014
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos, Aarti Singh, Larry Wasserman

* 25 pages, 5 figures 

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Confidence sets for persistence diagrams


Nov 20, 2014
Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry Wasserman, Sivaraman Balakrishnan, Aarti Singh

* Annals of Statistics 2014, Vol. 42, No. 6, 2301-2339 
* Published in at http://dx.doi.org/10.1214/14-AOS1252 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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On Estimating $L_2^2$ Divergence


Oct 30, 2014
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman


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Nonparametric ridge estimation


Aug 28, 2014
Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry Wasserman

* Annals of Statistics, Vol. 42, No. 4, 1511-1545 (2014) 
* Published in at http://dx.doi.org/10.1214/14-AOS1218 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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