Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Geometric Entropic Exploration

Jan 07, 2021
Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Avila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos


  Access Paper or Ask Questions

Improved Sample Complexity for Incremental Autonomous Exploration in MDPs

Dec 29, 2020
Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric

* NeurIPS 2020 

  Access Paper or Ask Questions

Game Plan: What AI can do for Football, and What Football can do for AI

Nov 18, 2020
Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adria Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Perolat, Bart De Vylder, Ali Eslami, Mark Rowland, Andrew Jaegle, Remi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis


  Access Paper or Ask Questions

BYOL works even without batch statistics

Oct 20, 2020
Pierre H. Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel Smith, Soham De, Razvan Pascanu, Bilal Piot, Michal Valko


  Access Paper or Ask Questions

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited

Oct 07, 2020
Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko


  Access Paper or Ask Questions

Fast active learning for pure exploration in reinforcement learning

Jul 27, 2020
Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko


  Access Paper or Ask Questions

Monte-Carlo Tree Search as Regularized Policy Optimization

Jul 24, 2020
Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Rémi Munos

* Accepted to International Conference on Machine Learning (ICML), 2020 

  Access Paper or Ask Questions

A Provably Efficient Sample Collection Strategy for Reinforcement Learning

Jul 13, 2020
Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric


  Access Paper or Ask Questions

A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces

Jul 09, 2020
Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko


  Access Paper or Ask Questions

Gamification of Pure Exploration for Linear Bandits

Jul 02, 2020
Rémy Degenne, Pierre Ménard, Xuedong Shang, Michal Valko

* 11+25 pages. To be published in the proceedings of ICML 2020 

  Access Paper or Ask Questions

Sampling from a $k$-DPP without looking at all items

Jun 30, 2020
Daniele Calandriello, Michał Dereziński, Michal Valko


  Access Paper or Ask Questions

Stochastic bandits with arm-dependent delays

Jun 18, 2020
Anne Gael Manegueu, Claire Vernade, Alexandra Carpentier, Michal Valko

* 19 Pages, 4 figures 

  Access Paper or Ask Questions

Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

Jun 13, 2020
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko


  Access Paper or Ask Questions

Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits

Jun 11, 2020
Pierre Perrault, Etienne Boursier, Vianney Perchet, Michal Valko


  Access Paper or Ask Questions

Adaptive Reward-Free Exploration

Jun 11, 2020
Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko


  Access Paper or Ask Questions

Planning in Markov Decision Processes with Gap-Dependent Sample Complexity

Jun 10, 2020
Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko


  Access Paper or Ask Questions

Regret Bounds for Kernel-Based Reinforcement Learning

Apr 12, 2020
Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko


  Access Paper or Ask Questions

Taylor Expansion Policy Optimization

Mar 13, 2020
Yunhao Tang, Michal Valko, Rémi Munos


  Access Paper or Ask Questions

Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification

Feb 26, 2020
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco


  Access Paper or Ask Questions

No-Regret Exploration in Goal-Oriented Reinforcement Learning

Jan 30, 2020
Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric


  Access Paper or Ask Questions

Multiagent Evaluation under Incomplete Information

Oct 30, 2019
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Perolat, Michal Valko, Georgios Piliouras, Remi Munos


  Access Paper or Ask Questions

Fixed-Confidence Guarantees for Bayesian Best-Arm Identification

Oct 28, 2019
Xuedong Shang, Rianne de Heide, Emilie Kaufmann, Pierre Ménard, Michal Valko


  Access Paper or Ask Questions

Derivative-Free & Order-Robust Optimisation

Oct 22, 2019
Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou Ammar


  Access Paper or Ask Questions