Victor-Emmanuel Brunel
14 papers · 2017–2025 · 8 conferences · across top CS/AI conferences
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Conferences
COLT (3)
AISTATS (2)
ALT (2)
ICML (2)
NIPS (2)
ICLR (1)
JMLR (1)
UAI (1)
Top co-authors
Keywords
determinantal point process
(4)
concentration inequality
(3)
method of moment
(2)
sample complexity
(2)
metric space
(2)
robust estimation
(1)
robust statistics
(1)
probabilistic modeling
(1)
kernel matrix
(1)
asymptotic variance
(1)
off-policy learning
(1)
curse of dimensionality
(1)
information retrieval
(1)
maximum likelihood estimation
(1)
rate of convergence
(1)
maximum likelihood
(1)
combinatorial algorithm
(1)
subset selection
(1)
best arm identification
(1)
frechet mean
(1)
Papers
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces
AISTATS 2025
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
UAI 2024
Concentration of empirical barycenters in metric spaces
ALT 2024
Geodesically convex $M$-estimation in metric spaces
COLT 2023
Exponential Smoothing for Off-Policy Learning
ICML 2023
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
ICLR 2021
Statistical guarantees for generative models without domination
ALT 2021
A nonasymptotic law of iterated logarithm for general M-estimators
AISTATS 2020
Learning rates for Gaussian mixtures under group action
COLT 2019
Learning Nonsymmetric Determinantal Point Processes
NIPS 2019
Best Arm Identification for Contaminated Bandits
JMLR 2019
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem
NIPS 2018
Rates of estimation for determinantal point processes
COLT 2017
Learning Determinantal Point Processes with Moments and Cycles
ICML 2017