Vernade, Claire

28 publications

L4DC 2025 A Pontryagin Perspective on Reinforcement Learning Onno Eberhard, Claire Vernade, Michael Muehlebach

NeurIPS 2025 Non-Stationary Lipschitz Bandits Nicolas Nguyen, Solenne Gaucher, Claire Vernade

ICML 2025 Partially Observable Reinforcement Learning with Memory Traces Onno Eberhard, Michael Muehlebach, Claire Vernade

AISTATS 2025 Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits Nicolas Nguyen, Imad Aouali, András György, Claire Vernade

NeurIPS 2025 Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning Amir Rezaei Balef, Claire Vernade, Katharina Eggensperger

NeurIPS 2025 Quantization-Free Autoregressive Action Transformer Ziyad Sheebaelhamd, Michael Tschannen, Michael Muehlebach, Claire Vernade

ICMLW 2024 A Pontryagin Perspective on Reinforcement Learning Onno Eberhard, Claire Vernade, Michael Muehlebach

ALT 2024 Algorithmic Learning Theory 2024: Preface Claire Vernade, Daniel Hsu

ICLRW 2024 Towards Bandit-Based Optimization for Automated Machine Learning Amir Rezaei Balef, Claire Vernade, Katharina Eggensperger

NeurIPS 2023 Beyond Average Return in Markov Decision Processes Alexandre Marthe, Aurélien Garivier, Claire Vernade

TMLR 2023 POMRL: No-Regret Learning-to-Plan with Increasing Horizons Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy

NeurIPSW 2023 POMRL: No-Regret Learning-to-Plan with Increasing Horizons Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy

ICLR 2022 EigenGame Unloaded: When Playing Games Is Better than Optimizing Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

ICLRW 2022 EigenGame Unloaded: When Playing Games Is Better than Optimizing Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

AISTATS 2021 Confident Off-Policy Evaluation and Selection Through Self-Normalized Importance Weighting Ilja Kuzborskij, Claire Vernade, Andras Gyorgy, Csaba Szepesvari

COLT 2021 Asymptotically Optimal Information-Directed Sampling Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvari

ICLR 2021 EigenGame: PCA as a Nash Equilibrium Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

ICML 2020 Linear Bandits with Stochastic Delayed Feedback Claire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brückner

ICML 2020 Non-Stationary Delayed Bandits with Intermediate Observations Claire Vernade, Andras Gyorgy, Timothy Mann

ALT 2020 Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes

ICML 2020 Stochastic Bandits with Arm-Dependent Delays Manegueu Anne Gael, Claire Vernade, Alexandra Carpentier, Michal Valko

NeurIPS 2019 Weighted Linear Bandits for Non-Stationary Environments Yoan Russac, Claire Vernade, Olivier Cappé

IJCAI 2017 Bernoulli Rank-1 Bandits for Click Feedback Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen

ECML-PKDD 2017 Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade

COLT 2017 Sparse Stochastic Bandits Joon Kwon, Vianney Perchet, Claire Vernade

UAI 2017 Stochastic Bandit Models for Delayed Conversions Claire Vernade, Olivier Cappé, Vianney Perchet

AISTATS 2017 Stochastic Rank-1 Bandits Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen

NeurIPS 2016 Multiple-Play Bandits in the Position-Based Model Paul Lagrée, Claire Vernade, Olivier Cappe