Marc Abeille

According to our database1, Marc Abeille authored at least 15 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Near-continuous time Reinforcement Learning for continuous state-action spaces.
Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023
Diffusive Limit Approximation of Pure-Jump Optimal Stochastic Control Problems.
J. Optim. Theory Appl., 2023

2022
Jointly Efficient and Optimal Algorithms for Logistic Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Regret Bounds for Generalized Linear Bandits under Parameter Drift.
CoRR, 2021

A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions.
Proceedings of the Algorithmic Learning Theory, 2021

Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Improved Optimistic Algorithms for Logistic Bandits.
Proceedings of the 37th International Conference on Machine Learning, 2020

Real-Time Optimisation for Online Learning in Auctions.
Proceedings of the 37th International Conference on Machine Learning, 2020

Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Thompson Sampling in Non-Episodic Restless Bandits.
CoRR, 2019

2018
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems.
CoRR, 2018

Explicit shading strategies for repeated truthful auctions.
CoRR, 2018

Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Thompson Sampling for Linear-Quadratic Control Problems.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Linear Thompson Sampling Revisited.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017


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