News, events & seminars

 

This page contains:

News

Seminars

  • 1 October 2021: rlberry: A Reinforcement Learning Library for Research and Education, Omar Darwiche Domingues (Inria Scool).
  • 24 September 2021: On the efficiency of subsampling algorithms for exploration in bandit, Dorian Baudry (Inria Scool).
  • 9 July 2021: M-estimation and Median of Means applied to statistical learning,
    Timothée Mathieu (Université Paris-Saclay).
  • 25 June 2021: Problem-Dependent Regret Lower Bounds for Finite-Horizon MDPs, Andrea Tirinzoni  (Scool).
  • 18 June 2021: New insights on concentrations inequalities for martingales,
    applications to statistics and machine learning, Taieb Touati (Sorbonne Université).
  • 11 June 2021: Reinforcement Learning in Non-Stationary Markov Decision Processes, Erwan Lecarpentier (ISAE-SUPAERO).
  • 21 May 2021: Cooperation in Online Learning, Riccardo Della Vecchia (Bocconi U. Milan).
  • 23 April 2021: Q-Learning algorithms and algorithmic collusion in online markets, by Luc Rocher (Imperial College London).
  • 9 April 2021: Restless stochastic bandits with correlations (arXiv), by Oleksandr Zadorozhnyi (University of Potsdam).
  • 2 April 2021: Causal Populations Identification through Hidden Distributions Estimation, by Céline Béji (Paris-Dauphine).
  • 29 January 2021: Predicting the clinical worsening of Covidom patients from their symptoms, by Jill-Jênn Vie, Vianney Taquet and Clémence Léguillette (Inria Scool).
  • 15 January 2021: Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling, by Nathan Grinsztajn (Inria Scool).
  • 4 January 2021: Solving stochastic bandits with an adversarial game, by Rémy Degenne (Inria Scool).
  • 27 November 2020: What is a Mean Field Game? Why is it interesting for Multi-agent RL? Why RL can also help to solve Mean Field Games?, by Sarah Perrin (Inria Scool).
  • 20 November 2020: High-Probability Regret Bounds for Online Linear Regression, by Reda Ouhamma (Inria Scool).

Report of activities

Comments are closed.