Victor-Emmanuel Brunel

According to our database1, Victor-Emmanuel Brunel authored at least 14 papers between 2017 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.
CoRR, 2024

2023
Exponential Smoothing for Off-Policy Learning.
Proceedings of the International Conference on Machine Learning, 2023

Geodesically convex M-estimation in metric spaces.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2021
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes.
Proceedings of the 9th International Conference on Learning Representations, 2021

Statistical guarantees for generative models without domination.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Propose, Test, Release: Differentially private estimation with high probability.
CoRR, 2020

A nonasymptotic law of iterated logarithm for general M-estimators.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Best Arm Identification for Contaminated Bandits.
J. Mach. Learn. Res., 2019

A nonasymptotic law of iterated logarithm for robust online estimators.
CoRR, 2019

Learning Nonsymmetric Determinantal Point Processes.
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.
Proceedings of the Conference on Learning Theory, 2019

2018
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem.
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.
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


  Loading...