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Journal Articles
- 2019
[j1]Jason M. Altschuler, Victor-Emmanuel Brunel, Alan Malek:
Best Arm Identification for Contaminated Bandits. J. Mach. Learn. Res. 20: 91:1-91:39 (2019)
Conference and Workshop Papers
- 2024
- [c11]Victor-Emmanuel Brunel, Jordan Serres:
Concentration of empirical barycenters in metric spaces. ALT 2024: 337-361 - 2023
- [c10]Victor-Emmanuel Brunel:
Geodesically convex M-estimation in metric spaces. COLT 2023: 2188-2210 - [c9]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Exponential Smoothing for Off-Policy Learning. ICML 2023: 984-1017 - 2021
- [c8]Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak S. Dalalyan:
Statistical guarantees for generative models without domination. ALT 2021: 1051-1071 - [c7]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR 2021 - 2020
- [c6]Arnak S. Dalalyan, Nicolas Schreuder, Victor-Emmanuel Brunel:
A nonasymptotic law of iterated logarithm for general M-estimators. AISTATS 2020: 1331-1341 - 2019
- [c5]Victor-Emmanuel Brunel:
Learning rates for Gaussian mixtures under group action. COLT 2019: 471-491 - [c4]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene:
Learning Nonsymmetric Determinantal Point Processes. NeurIPS 2019: 6715-6725 - 2018
- [c3]Victor-Emmanuel Brunel:
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem. NeurIPS 2018: 7376-7385 - 2017
- [c2]Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John C. Urschel:
Rates of estimation for determinantal point processes. COLT 2017: 343-345 - [c1]John C. Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet:
Learning Determinantal Point Processes with Moments and Cycles. ICML 2017: 3511-3520
Informal and Other Publications
- 2024
- [i8]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. CoRR abs/2402.14664 (2024) - [i7]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. CoRR abs/2406.03434 (2024) - 2023
- [i6]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Exponential Smoothing for Off-Policy Learning. CoRR abs/2305.15877 (2023) - 2020
- [i5]Victor-Emmanuel Brunel, Marco Avella-Medina:
Propose, Test, Release: Differentially private estimation with high probability. CoRR abs/2002.08774 (2020) - [i4]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR abs/2006.09862 (2020) - 2019
- [i3]Victor-Emmanuel Brunel, Arnak S. Dalalyan, Nicolas Schreuder:
A nonasymptotic law of iterated logarithm for robust online estimators. CoRR abs/1903.06576 (2019) - [i2]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene
:
Learning Nonsymmetric Determinantal Point Processes. CoRR abs/1905.12962 (2019) - 2018
- [i1]Jason M. Altschuler, Victor-Emmanuel Brunel, Alan Malek:
Best Arm Identification for Contaminated Bandits. CoRR abs/1802.09514 (2018)
Coauthor Index
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