Victor-Emmanuel Brunel

According to our database, Victor-Emmanuel Brunel authored at least 16 papers between 2017 and 2024.

Collaborative distances:

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

2024

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

CoRR, 2024

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

CoRR, 2024

Concentration of empirical barycenters in metric spaces.

Victor-Emmanuel Brunel, Jordan Serres

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Exponential Smoothing for Off-Policy Learning.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

Proceedings of the International Conference on Machine Learning, 2023

Geodesically convex M-estimation in metric spaces.

Victor-Emmanuel Brunel

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2021

Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes.

Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel

Proceedings of the 9th International Conference on Learning Representations, 2021

Statistical guarantees for generative models without domination.

Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak S. Dalalyan

Proceedings of the Algorithmic Learning Theory, 2021

2020

Propose, Test, Release: Differentially private estimation with high probability.

Victor-Emmanuel Brunel, Marco Avella-Medina

CoRR, 2020

A nonasymptotic law of iterated logarithm for general M-estimators.

Arnak S. Dalalyan, Nicolas Schreuder, Victor-Emmanuel Brunel

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Best Arm Identification for Contaminated Bandits.

Jason M. Altschuler, Victor-Emmanuel Brunel, Alan Malek

J. Mach. Learn. Res., 2019

A nonasymptotic law of iterated logarithm for robust online estimators.

Victor-Emmanuel Brunel, Arnak S. Dalalyan, Nicolas Schreuder

CoRR, 2019

Learning Nonsymmetric Determinantal Point Processes.

Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene

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

Learning rates for Gaussian mixtures under group action.

Victor-Emmanuel Brunel

Proceedings of the Conference on Learning Theory, 2019

2018

Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem.

Victor-Emmanuel Brunel

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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