Philippe Rigollet

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 56

Top Topics

Point Processes

Online Learning

Density Estimators

Top Venues

Publications

Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
The emergence of clusters in self-attention dynamics. CoRR (2023)
Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
The emergence of clusters in self-attention dynamics. NeurIPS (2023)
Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
A mathematical perspective on Transformers. CoRR (2023)
Subhroshekhar Ghosh, Philippe Rigollet
Sparse Multi-Reference Alignment: Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem. Found. Comput. Math. 23 (5) (2023)
Yuling Yan, Kaizheng Wang, Philippe Rigollet
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow. CoRR (2023)
Marie Breeur, George Stepaniants, Pekka Keski-Rahkonen, Philippe Rigollet, Vivian Viallon
Optimal transport for automatic alignment of untargeted metabolomic data. CoRR (2023)
Yanjun Han, Philippe Rigollet, George Stepaniants
Covariance alignment: from maximum likelihood estimation to Gromov-Wasserstein. CoRR (2023)
Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery. AISTATS (2023)
Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic
An algorithmic solution to the Blotto game using multi-marginal couplings. CoRR (2022)
Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
Variational inference via Wasserstein gradient flows. NeurIPS (2022)
Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
Gaussian discrepancy: A probabilistic relaxation of vector balancing. Discret. Appl. Math. 322 (2022)
Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
Variational inference via Wasserstein gradient flows. CoRR (2022)
Enric Boix Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
GULP: a prediction-based metric between representations. CoRR (2022)
Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
Rejection sampling from shape-constrained distributions in sublinear time. AISTATS (2022)
Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic
An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings. EC (2022)
Enric Boix-Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
GULP: a prediction-based metric between representations. NeurIPS (2022)
Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
The query complexity of sampling from strongly log-concave distributions in one dimension. COLT (2022)
Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
Gaussian discrepancy: a probabilistic relaxation of vector balancing. CoRR (2021)
Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin Stromme
Fast and Smooth Interpolation on Wasserstein Space. AISTATS (2021)
Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. COLT (2021)
Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
The query complexity of sampling from strongly log-concave distributions in one dimension. CoRR (2021)
Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
Rejection sampling from shape-constrained distributions in sublinear time. CoRR (2021)
Subhro Ghosh, Philippe Rigollet
Gaussian Determinantal Processes: a new model for directionality in data. CoRR (2021)
Paxton Turner, Jingbo Liu, Philippe Rigollet
Efficient Interpolation of Density Estimators. AISTATS (2021)
Subhro Ghosh, Philippe Rigollet
Multi-Reference Alignment for sparse signals, Uniform Uncertainty Principles and the Beltway Problem. CoRR (2021)
Paxton Turner, Jingbo Liu, Philippe Rigollet
A Statistical Perspective on Coreset Density Estimation. AISTATS (2021)
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin Stromme
Exponential ergodicity of mirror-Langevin diffusions. NeurIPS (2020)
Paxton Turner, Jingbo Liu, Philippe Rigollet
Efficient Interpolation of Density Estimators. CoRR (2020)
Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
Gradient descent algorithms for Bures-Wasserstein barycenters. COLT (2020)
Jan-Christian Hütter, Philippe Rigollet
Estimation Rates for Sparse Linear Cyclic Causal Models. UAI (2020)
Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. CoRR (2020)
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. CoRR (2020)
Paxton Turner, Jingbo Liu, Philippe Rigollet
A Statistical Perspective on Coreset Density Estimation. CoRR (2020)
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. NeurIPS (2020)
Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin Stromme
Exponential ergodicity of mirror-Langevin diffusions. CoRR (2020)
Paxton Turner, Raghu Meka, Philippe Rigollet
Balancing Gaussian vectors in high dimension. COLT (2020)
Jingbo Liu, Philippe Rigollet
Power analysis of knockoff filters for correlated designs. CoRR (2019)
Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, Elina Robeva
Estimation of Monge Matrices. CoRR (2019)
Raghu Meka, Philippe Rigollet, Paxton Turner
Balancing Gaussian vectors in high dimension. CoRR (2019)
Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer
The Sample Complexity of Multireference Alignment. SIAM J. Math. Data Sci. 1 (3) (2019)
Jingbo Liu, Philippe Rigollet
Power analysis of knockoff filters for correlated designs. NeurIPS (2019)
Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Philippe Rigollet, Geoffrey Schiebinger, Jonathan Weed
Statistical Optimal Transport via Factored Couplings. AISTATS (2019)
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
Teacher Improves Learning by Selecting a Training Subset. CoRR (2018)
Nilin Abrahamsen, Philippe Rigollet
Sparse Gaussian ICA. CoRR (2018)
Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Geoffrey Schiebinger, Philippe Rigollet, Jonathan Weed
Statistical Optimal Transport via Geodesic Hubs. CoRR (2018)
Sébastien Bubeck, Philippe Rigollet
Conference on Learning Theory 2018: Preface. COLT (2018)
Cheng Mao, Jonathan Weed, Philippe Rigollet
Minimax Rates and Efficient Algorithms for Noisy Sorting. ALT (2018)
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
Teacher Improves Learning by Selecting a Training Subset. AISTATS (2018)
John C. Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet
Learning Determinantal Point Processes with Moments and Cycles. ICML (2017)
Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John C. Urschel
Rates of estimation for determinantal point processes. COLT (2017)
Cheng Mao, Jonathan Weed, Philippe Rigollet
Minimax Rates and Efficient Algorithms for Noisy Sorting. CoRR (2017)
Jason Altschuler, Jonathan Weed, Philippe Rigollet
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. NIPS (2017)
Jason Altschuler, Jonathan Weed, Philippe Rigollet
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. CoRR (2017)
Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer
The sample complexity of multi-reference alignment. CoRR (2017)
Quentin Berthet, Philippe Rigollet, Piyush Srivastava
Exact recovery in the Ising blockmodel. CoRR (2016)
Jonathan Weed, Vianney Perchet, Philippe Rigollet
Online learning in repeated auctions. COLT (2016)
Jonathan Weed, Vianney Perchet, Philippe Rigollet
Online learning in repeated auctions. CoRR (2015)
Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg
Batched Bandit Problems. COLT (2015)
Dong Dai, Philippe Rigollet, Lucy Xia, Tong Zhang
Aggregation of Affine Estimators. CoRR (2013)
Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
Bounded regret in stochastic multi-armed bandits CoRR (2013)
Quentin Berthet, Philippe Rigollet
Computational Lower Bounds for Sparse PCA CoRR (2013)
Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
Bounded regret in stochastic multi-armed bandits. COLT (2013)
Quentin Berthet, Philippe Rigollet
Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. COLT (2013)
Dong Dai, Philippe Rigollet, Tong Zhang
Deviation Optimal Learning using Greedy Q-aggregation CoRR (2012)
Philippe Rigollet, Xin Tong
Neyman-Pearson classification, convexity and stochastic constraints CoRR (2011)
Philippe Rigollet, Xin Tong
Neyman-Pearson classification under a strict constraint. COLT (2011)
Philippe Rigollet, Xin Tong
Neyman-Pearson Classification, Convexity and Stochastic Constraints. J. Mach. Learn. Res. 12 (2011)
Vianney Perchet, Philippe Rigollet
The multi-armed bandit problem with covariates CoRR (2011)
Philippe Rigollet, Assaf Zeevi
Nonparametric Bandits with Covariates. COLT (2010)
Philippe Rigollet
Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption. J. Mach. Learn. Res. 8 (2007)
Philippe Rigollet
Generalization error bounds in semi-supervised classification under the cluster assumption CoRR (2006)