Philippe Rigollet

According to our database1, Philippe Rigollet authored at least 42 papers between 2007 and 2022.

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Bibliography

2022
Variational inference via Wasserstein gradient flows.
CoRR, 2022

An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

The query complexity of sampling from strongly log-concave distributions in one dimension.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Rejection sampling from shape-constrained distributions in sublinear time.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Gaussian Determinantal Processes: a new model for directionality in data.
CoRR, 2021

Gaussian discrepancy: a probabilistic relaxation of vector balancing.
CoRR, 2021

Multi-Reference Alignment for sparse signals, Uniform Uncertainty Principles and the Beltway Problem.
CoRR, 2021

Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm.
Proceedings of the Conference on Learning Theory, 2021

A Statistical Perspective on Coreset Density Estimation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Efficient Interpolation of Density Estimators.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Fast and Smooth Interpolation on Wasserstein Space.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Estimation Rates for Sparse Linear Cyclic Causal Models.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Exponential ergodicity of mirror-Langevin diffusions.
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.
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.
Proceedings of the Conference on Learning Theory, 2020

Gradient descent algorithms for Bures-Wasserstein barycenters.
Proceedings of the Conference on Learning Theory, 2020

2019
The Sample Complexity of Multireference Alignment.
SIAM J. Math. Data Sci., 2019

Estimation of Monge Matrices.
CoRR, 2019

Power analysis of knockoff filters for correlated designs.
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.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Statistical Optimal Transport via Geodesic Hubs.
CoRR, 2018

Sparse Gaussian ICA.
CoRR, 2018

Conference on Learning Theory 2018: Preface.
Proceedings of the Conference On Learning Theory, 2018

Minimax Rates and Efficient Algorithms for Noisy Sorting.
Proceedings of the Algorithmic Learning Theory, 2018

Teacher Improves Learning by Selecting a Training Subset.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
The sample complexity of multi-reference alignment.
CoRR, 2017

Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration.
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.
Proceedings of the 34th International Conference on Machine Learning, 2017

Rates of estimation for determinantal point processes.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Exact recovery in the Ising blockmodel.
CoRR, 2016

Online learning in repeated auctions.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Batched Bandit Problems.
Proceedings of The 28th Conference on Learning Theory, 2015

2013
Computational Lower Bounds for Sparse PCA
CoRR, 2013

Aggregation of Affine Estimators.
CoRR, 2013

Bounded regret in stochastic multi-armed bandits.
Proceedings of the COLT 2013, 2013

Complexity Theoretic Lower Bounds for Sparse Principal Component Detection.
Proceedings of the COLT 2013, 2013

2012
Deviation Optimal Learning using Greedy Q-aggregation
CoRR, 2012

2011
Neyman-Pearson Classification, Convexity and Stochastic Constraints.
J. Mach. Learn. Res., 2011

Neyman-Pearson classification under a strict constraint.
Proceedings of the COLT 2011, 2011

The multi-armed bandit problem with covariates
CoRR, 2011

2010
Nonparametric Bandits with Covariates.
Proceedings of the COLT 2010, 2010

2007
Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption.
J. Mach. Learn. Res., 2007


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