Brunel, Victor-Emmanuel

14 publications

AISTATS 2025 Bayesian Off-Policy Evaluation and Learning for Large Action Spaces Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

ALT 2024 Concentration of Empirical Barycenters in Metric Spaces Victor-Emmanuel Brunel, Jordan Serres

UAI 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

ICML 2023 Exponential Smoothing for Off-Policy Learning Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

COLT 2023 Geodesically Convex $m$-Estimation in Metric Spaces Victor-Emmanuel Brunel

ICLR 2021 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel

ALT 2021 Statistical Guarantees for Generative Models Without Domination Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan

AISTATS 2020 A Nonasymptotic Law of Iterated Logarithm for General M-Estimators Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan

JMLR 2019 Best Arm Identification for Contaminated Bandits Jason Altschuler, Victor-Emmanuel Brunel, Alan Malek

NeurIPS 2019 Learning Nonsymmetric Determinantal Point Processes Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene

COLT 2019 Learning Rates for Gaussian Mixtures Under Group Action Victor-Emmanuel Brunel

NeurIPS 2018 Learning Signed Determinantal Point Processes Through the Principal Minor Assignment Problem Victor-Emmanuel Brunel

ICML 2017 Learning Determinantal Point Processes with Moments and Cycles John Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet

COLT 2017 Rates of Estimation for Determinantal Point Processes Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John Urschel