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 | 774 | 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 | 632 | 2017 |
Complexity theoretic lower bounds for sparse principal component detection Q Berthet, P Rigollet Conference on learning theory, 1046-1066, 2013 | 385* | 2013 |
Optimal detection of sparse principal components in high dimension Q Berthet, P Rigollet | 336 | 2013 |
High-dimensional statistics P Rigollet, JC Hütter arXiv preprint arXiv:2310.19244, 2023 | 289* | 2023 |
Exponential screening and optimal rates of sparse estimation P Rigollet, A Tsybakov The Annals of Statistics 39 (2), 731-771, 2011 | 273 | 2011 |
Batched bandit problems V Perchet, P Rigollet, S Chassang, E Snowberg | 246 | 2016 |
Generalization error bounds in semi-supervised classification under the cluster assumption P Rigollet Arxiv preprint math/0604233, 2006 | 218 | 2006 |
The multi-armed bandit problem with covariates V Perchet, P Rigollet | 201 | 2013 |
Learning by mirror averaging A Juditsky, P Rigollet, AB Tsybakov The Annals of Statistics 36 (5), 2183-2206, 2008 | 189 | 2008 |
Optimal rates for plug-in estimators of density level sets P Rigollet, R Vert Bernoulli 15 (4), 1154-1178, 2009 | 148 | 2009 |
Sparse estimation by exponential weighting P Rigollet, A Tsybakov Statistical Science 27 (4), 558-575, 2012 | 141 | 2012 |
Linear and convex aggregation of density estimators P Rigollet, AB Tsybakov Mathematical Methods of Statistics 16, 260-280, 2007 | 139 | 2007 |
Nonparametric bandits with covariates P Rigollet, A Zeevi arXiv preprint arXiv:1003.1630, 2010 | 130 | 2010 |
Bounded regret in stochastic multi-armed bandits S Bubeck, V Perchet, P Rigollet Conference on Learning Theory, 122-134, 2013 | 113 | 2013 |
Neyman-pearson classification, convexity and stochastic constraints P Rigollet, X Tong Journal of machine learning research, 2011 | 113 | 2011 |
Minimax estimation of smooth optimal transport maps JC Hütter, P Rigollet | 106 | 2021 |
Estimation of wasserstein distances in the spiked transport model J Niles-Weed, P Rigollet Bernoulli 28 (4), 2663-2688, 2022 | 105 | 2022 |
Optimal rates for total variation denoising JC Hütter, P Rigollet Conference on Learning Theory, 1115-1146, 2016 | 105 | 2016 |
Kullback-Leibler aggregation and misspecified generalized linear models P Rigollet Arxiv preprint arXiv:0911.2919, 2009 | 102 | 2009 |