Philippe Rigollet

According to our database, Philippe Rigollet authored at least 52 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

An Algorithmic Solution to the Blotto Game Using Multimarginal Couplings.

Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic

Oper. Res., 2024

Dynamic metastability in the self-attention model.

Borjan Geshkovski, Hugo Koubbi, Yury Polyanskiy, Philippe Rigollet

CoRR, 2024

2023

Sparse Multi-Reference Alignment: Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem.

Subhroshekhar Ghosh, Philippe Rigollet

Found. Comput. Math., October, 2023

A mathematical perspective on Transformers.

Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet

CoRR, 2023

Covariance alignment: from maximum likelihood estimation to Gromov-Wasserstein.

Yanjun Han, Philippe Rigollet, George Stepaniants

CoRR, 2023

Optimal transport for automatic alignment of untargeted metabolomic data.

Marie Breeur, George Stepaniants, Pekka Keski-Rahkonen, Philippe Rigollet, Vivian Viallon

CoRR, 2023

Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow.

Yuling Yan, Kaizheng Wang, Philippe Rigollet

CoRR, 2023

The emergence of clusters in self-attention dynamics.

Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery.

Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Gaussian discrepancy: A probabilistic relaxation of vector balancing.

Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner

Discret. Appl. Math., 2022

An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings.

Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic

Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Variational inference via Wasserstein gradient flows.

Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GULP: a prediction-based metric between representations.

Enric Boix-Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The query complexity of sampling from strongly log-concave distributions in one dimension.

Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Rejection sampling from shape-constrained distributions in sublinear time.

Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Gaussian Determinantal Processes: a new model for directionality in data.

Subhro Ghosh, Philippe Rigollet

CoRR, 2021

Multi-Reference Alignment for sparse signals, Uniform Uncertainty Principles and the Beltway Problem.

Subhro Ghosh, Philippe Rigollet

CoRR, 2021

Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm.

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

Proceedings of the Conference on Learning Theory, 2021

A Statistical Perspective on Coreset Density Estimation.

Paxton Turner, Jingbo Liu, Philippe Rigollet

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Efficient Interpolation of Density Estimators.

Paxton Turner, Jingbo Liu, Philippe Rigollet

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Fast and Smooth Interpolation on Wasserstein Space.

Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin J. Stromme

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Estimation Rates for Sparse Linear Cyclic Causal Models.

Jan-Christian Hütter, Philippe Rigollet

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Exponential ergodicity of mirror-Langevin diffusions.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Balancing Gaussian vectors in high dimension.

Paxton Turner, Raghu Meka, Philippe Rigollet

Proceedings of the Conference on Learning Theory, 2020

Gradient descent algorithms for Bures-Wasserstein barycenters.

Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme

Proceedings of the Conference on Learning Theory, 2020

2019

The Sample Complexity of Multireference Alignment.

Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer

SIAM J. Math. Data Sci., 2019

Estimation of Monge Matrices.

Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, Elina Robeva

CoRR, 2019

Power analysis of knockoff filters for correlated designs.

Jingbo Liu, Philippe Rigollet

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Statistical Optimal Transport via Factored Couplings.

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

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Statistical Optimal Transport via Geodesic Hubs.

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

CoRR, 2018

Sparse Gaussian ICA.

Nilin Abrahamsen, Philippe Rigollet

CoRR, 2018

Conference on Learning Theory 2018: Preface.

Sébastien Bubeck, Philippe Rigollet

Proceedings of the Conference On Learning Theory, 2018

Minimax Rates and Efficient Algorithms for Noisy Sorting.

Cheng Mao, Jonathan Weed, Philippe Rigollet

Proceedings of the Algorithmic Learning Theory, 2018

Teacher Improves Learning by Selecting a Training Subset.

Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

The sample complexity of multi-reference alignment.

Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer

CoRR, 2017

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

Jason M. Altschuler, Jonathan Weed, Philippe Rigollet

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Determinantal Point Processes with Moments and Cycles.

John C. Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet

Proceedings of the 34th International Conference on Machine Learning, 2017

Rates of estimation for determinantal point processes.

Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John C. Urschel

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Exact recovery in the Ising blockmodel.

Quentin Berthet, Philippe Rigollet, Piyush Srivastava

CoRR, 2016

Online learning in repeated auctions.

Jonathan Weed, Vianney Perchet, Philippe Rigollet

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Batched Bandit Problems.

Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg

Proceedings of The 28th Conference on Learning Theory, 2015

2013

Computational Lower Bounds for Sparse PCA

Quentin Berthet, Philippe Rigollet

CoRR, 2013

Aggregation of Affine Estimators.

Dong Dai, Philippe Rigollet, Lucy Xia, Tong Zhang

CoRR, 2013

Bounded regret in stochastic multi-armed bandits.

Sébastien Bubeck, Vianney Perchet, Philippe Rigollet

Proceedings of the COLT 2013, 2013

Complexity Theoretic Lower Bounds for Sparse Principal Component Detection.

Quentin Berthet, Philippe Rigollet

Proceedings of the COLT 2013, 2013

2012

Deviation Optimal Learning using Greedy Q-aggregation

Dong Dai, Philippe Rigollet, Tong Zhang

CoRR, 2012

2011

Neyman-Pearson Classification, Convexity and Stochastic Constraints.

Philippe Rigollet, Xin Tong

J. Mach. Learn. Res., 2011

Neyman-Pearson classification under a strict constraint.

Philippe Rigollet, Xin Tong

Proceedings of the COLT 2011, 2011

The multi-armed bandit problem with covariates

Vianney Perchet, Philippe Rigollet

CoRR, 2011

2010

Nonparametric Bandits with Covariates.

Philippe Rigollet, Assaf Zeevi

Proceedings of the COLT 2010, 2010

2007

Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption.

Philippe Rigollet

J. Mach. Learn. Res., 2007