Philippe Rigollet

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	总计	2020 年至今
引用	7368	5109
h 指数	41	38
i10 指数	65	59

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Jonathan Niles-WeedNew York University在 cims.nyu.edu 的电子邮件经过验证
Jan-Christian HütterGenentech在 gene.com 的电子邮件经过验证
Sinho ChewiYale University在 yale.edu 的电子邮件经过验证
Thibaut Le GouicInstitut de Mathématiques de Marseille在 math.cnrs.fr 的电子邮件经过验证
Geoffrey SchiebingerUniversity of British Columbia在 math.ubc.ca 的电子邮件经过验证
Vianney PerchetCrest, ENSAE & Criteo AI Lab在 normalesup.org 的电子邮件经过验证
Quentin BerthetGoogle DeepMind, Paris在 google.com 的电子邮件经过验证
Austin J. StrommeENSAE, CREST在 ensae.fr 的电子邮件经过验证
Chen LuMIT在 mit.edu 的电子邮件经过验证
Brian ClearyAssistant Professor, Boston University在 bu.edu 的电子邮件经过验证
Cheng MaoGeorgia Institute of Technology在 math.gatech.edu 的电子邮件经过验证
Tyler MaunuBrandeis University在 brandeis.edu 的电子邮件经过验证
Anatoli JuditskyProfessor at Université Grenoble-Alpes在 univ-grenoble-alpes.fr 的电子邮件经过验证
Jason M. AltschulerUPenn在 upenn.edu 的电子邮件经过验证
Afonso S. BandeiraProfessor of Mathematics, ETH Zurich在 math.ethz.ch 的电子邮件经过验证
Paxton TurnerArbol Inc.在 alum.mit.edu 的电子邮件经过验证
George StepaniantsComputing and Mathematical Sciences, California Institute of Technology在 caltech.edu 的电子邮件经过验证
Xin TongAssociate Professor, Department of Data Sciences and Operations, University of Southern California在 marshall.usc.edu 的电子邮件经过验证
Erik SnowbergDavid Eccles School of Business, University of Utah在 eccles.utah.edu 的电子邮件经过验证
Sylvain ChassangProfessor of Economics, Princeton University在 princeton.edu 的电子邮件经过验证

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Philippe Rigollet

Massachusetts Institute of Technology

在 math.mit.edu 的电子邮件经过验证 - 首页

Statistics Machine Learning Optimal Transport


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming G Schiebinger, J Shu, M Tabaka, B Cleary, V Subramanian, A Solomon, ... Cell 176 (4), 928-943. e22, 2019	910	2019
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration J Altschuler, J Niles-Weed, P Rigollet Advances in neural information processing systems 30, 2017	711	2017
Complexity theoretic lower bounds for sparse principal component detection Q Berthet, P Rigollet Conference on learning theory, 1046-1066, 2013	389*	2013
Optimal detection of sparse principal components in high dimension Q Berthet, P Rigollet	355	2013
High-dimensional statistics P Rigollet, JC Hütter arXiv preprint arXiv:2310.19244, 2023	338*	2023
Exponential screening and optimal rates of sparse estimation P Rigollet, A Tsybakov The Annals of Statistics 39 (2), 731-771, 2011	280	2011
Batched bandit problems V Perchet, P Rigollet, S Chassang, E Snowberg	278	2016
Generalization error bounds in semi-supervised classification under the cluster assumption P Rigollet Arxiv preprint math/0604233, 2006	226	2006
The multi-armed bandit problem with covariates V Perchet, P Rigollet	215	2013
Learning by mirror averaging A Juditsky, P Rigollet, AB Tsybakov The Annals of Statistics 36 (5), 2183-2206, 2008	192	2008
Optimal rates for plug-in estimators of density level sets P Rigollet, R Vert Bernoulli 15 (4), 1154-1178, 2009	152	2009
Linear and convex aggregation of density estimators P Rigollet, AB Tsybakov Mathematical Methods of Statistics 16, 260-280, 2007	145	2007
Nonparametric bandits with covariates P Rigollet, A Zeevi arXiv preprint arXiv:1003.1630, 2010	142	2010
Sparse estimation by exponential weighting P Rigollet, A Tsybakov Statistical Science 27 (4), 558-575, 2012	141	2012
Minimax estimation of smooth optimal transport maps JC Hütter, P Rigollet	138	2021
Neyman-pearson classification, convexity and stochastic constraints P Rigollet, X Tong Journal of machine learning research, 2011	126	2011
Estimation of wasserstein distances in the spiked transport model J Niles-Weed, P Rigollet Bernoulli 28 (4), 2663-2688, 2022	121	2022
Bounded regret in stochastic multi-armed bandits S Bubeck, V Perchet, P Rigollet Conference on Learning Theory, 122-134, 2013	118	2013
Gradient descent algorithms for Bures-Wasserstein barycenters S Chewi, T Maunu, P Rigollet, AJ Stromme Conference on Learning Theory, 1276-1304, 2020	117	2020
Optimal rates for total variation denoising JC Hütter, P Rigollet Conference on Learning Theory, 1115-1146, 2016	113	2016

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