Orseau, Laurent

25 publications

NeurIPS 2025 Understanding Prompt Tuning and In-Context Learning via Meta-Learning Tim Genewein, Li Kevin Wenliang, Jordi Grau-Moya, Anian Ruoss, Laurent Orseau, Marcus Hutter

IJCAI 2024 Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner

ICLR 2024 Language Modeling Is Compression Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness

ICML 2024 Learning Universal Predictors Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Gregoire Deletang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness

NeurIPSW 2023 Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Tudor Berariu, Matej Balog, Gheorghe Comanici, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera Paredes, Laurent Orseau, Petar Veličković, Anurag Murty Naredla, Joonkyung Lee, Adam Zsolt Wagner, Doina Precup

IJCAI 2023 Levin Tree Search with Context Models Laurent Orseau, Marcus Hutter, Levi H. S. Lelis

ICML 2023 Memory-Based Meta-Learning on Non-Stationary Distributions Tim Genewein, Gregoire Deletang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness

ICML 2022 Proving Theorems Using Incremental Learning and Hindsight Experience Replay Eser Aygün, Ankit Anand, Laurent Orseau, Xavier Glorot, Stephen M Mcaleer, Vlad Firoiu, Lei M Zhang, Doina Precup, Shibl Mourad

AAAI 2021 Policy-Guided Heuristic Search with Guarantees Laurent Orseau, Levi H. S. Lelis

NeurIPS 2020 Avoiding Side Effects by Considering Future Tasks Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg

NeurIPS 2020 Logarithmic Pruning Is All You Need Laurent Orseau, Marcus Hutter, Omar Rivasplata

IJCAI 2020 Pitfalls of Learning a Reward Function Online Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg

ICML 2019 An Investigation of Model-Free Planning Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sebastien Racaniere, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy Lillicrap

IJCAI 2019 Iterative Budgeted Exponential Search Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant

NeurIPS 2018 Single-Agent Policy Tree Search with Guarantees Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber

IJCAI 2017 On Thompson Sampling and Asymptotic Optimality Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter

IJCAI 2017 Reinforcement Learning with a Corrupted Reward Channel Tom Everitt, Victoria Krakovna, Laurent Orseau, Shane Legg

ALT 2017 Soft-Bayes: Prod for Mixtures of Experts with Log-Loss Laurent Orseau, Tor Lattimore, Shane Legg

UAI 2016 Safely Interruptible Agents Laurent Orseau, Stuart Armstrong

UAI 2016 Thompson Sampling Is Asymptotically Optimal in General Environments Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter

IJCAI 2015 Online Learning of K-CNF Boolean Functions Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare

ALT 2013 Universal Knowledge-Seeking Agents for Stochastic Environments Laurent Orseau, Tor Lattimore, Marcus Hutter

ALT 2011 Universal Knowledge-Seeking Agents Laurent Orseau

ALT 2010 Optimality Issues of Universal Greedy Agents with Static Priors Laurent Orseau

IJCAI 2007 Learning to Count by Think Aloud Imitation Laurent Orseau