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Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm


Dec 23, 2020
Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet

* 41 pages 

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Efficient Interpolation of Density Estimators


Nov 10, 2020
Paxton Turner, Jingbo Liu, Philippe Rigollet


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A Statistical Perspective on Coreset Density Estimation


Nov 10, 2020
Paxton Turner, Jingbo Liu, Philippe Rigollet


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Projection to Fairness in Statistical Learning


Jun 25, 2020
Thibaut Le Gouic, Jean-Michel Loubes, Philippe Rigollet


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SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence


Jun 03, 2020
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet

* 20 pages, 5 figures 

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Exponential ergodicity of mirror-Langevin diffusions


Jun 02, 2020
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme

* 27 pages, 10 figures 

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Power analysis of knockoff filters for correlated designs


Oct 29, 2019
Jingbo Liu, Philippe Rigollet

* Accepted to Neurips 2019. The conference version includes the contents of this version excluding the appendices 

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Estimation of Monge Matrices


Apr 05, 2019
Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, Elina Robeva

* 42 pages, 3 figures 

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Statistical Optimal Transport via Factored Couplings


Oct 10, 2018
Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Philippe Rigollet, Geoffrey Schiebinger, Jonathan Weed

* 29 pages, 3 figures 

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Uncoupled isotonic regression via minimum Wasserstein deconvolution


Jun 27, 2018
Philippe Rigollet, Jonathan Weed


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Sparse Gaussian ICA


Apr 03, 2018
Nilin Abrahamsen, Philippe Rigollet

* Corrected typos 

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Teacher Improves Learning by Selecting a Training Subset


Feb 25, 2018
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu

* AISTATS 2018 

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Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration


Feb 07, 2018
Jason Altschuler, Jonathan Weed, Philippe Rigollet

* Advances in Neural Information Processing Systems 30 (NIPS 2017), 1961-1971 

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Minimax Rates and Efficient Algorithms for Noisy Sorting


Oct 28, 2017
Cheng Mao, Jonathan Weed, Philippe Rigollet

* 27 pages, 2 figures 

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Optimal Rates of Statistical Seriation


Aug 01, 2016
Nicolas Flammarion, Cheng Mao, Philippe Rigollet

* V2 corrects an error in Lemma A.1, v3 corrects appendix F on unimodal regression where the bounds now hold with polynomial probability rather than exponential 

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Online learning in repeated auctions


Nov 18, 2015
Jonathan Weed, Vianney Perchet, Philippe Rigollet


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Aggregation of Affine Estimators


Nov 12, 2013
Dong Dai, Philippe Rigollet, Lucy Xia, Tong Zhang


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Optimal detection of sparse principal components in high dimension


Sep 19, 2013
Quentin Berthet, Philippe Rigollet

* Annals of Statistics 2013, Vol. 41, No. 4, 1780-1815 
* Published in at http://dx.doi.org/10.1214/13-AOS1127 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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The multi-armed bandit problem with covariates


May 24, 2013
Vianney Perchet, Philippe Rigollet

* Annals of Statistics 2013, Vol. 41, No. 2, 693-721 
* Published in at http://dx.doi.org/10.1214/13-AOS1101 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Computational Lower Bounds for Sparse PCA


Apr 26, 2013
Quentin Berthet, Philippe Rigollet

* Alternate title: "Complexity Theoretic Lower Bounds for Sparse Principal Component Detection" 

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Bounded regret in stochastic multi-armed bandits


Feb 12, 2013
Sébastien Bubeck, Vianney Perchet, Philippe Rigollet


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Deviation optimal learning using greedy Q-aggregation


Dec 12, 2012
Dong Dai, Philippe Rigollet, Tong Zhang

* Annals of Statistics 2012, Vol. 40, No. 3, 1878-1905 
* Published in at http://dx.doi.org/10.1214/12-AOS1025 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Kullback-Leibler aggregation and misspecified generalized linear models


Jun 05, 2012
Philippe Rigollet

* Annals of Statistics 2012, Vol. 40, No. 2, 639-665 
* Published in at http://dx.doi.org/10.1214/11-AOS961 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Neyman-Pearson classification, convexity and stochastic constraints


Feb 28, 2011
Philippe Rigollet, Xin Tong


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Generalization error bounds in semi-supervised classification under the cluster assumption


Apr 11, 2006
Philippe Rigollet


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