Efficient Approximate Query Answering over Sensor Data with Deterministic Error Guarantees. - Jaqueline J. Brito; Korhan Demirkaya; Etienne Boursier; Yannis Katsis; Chunbin Lin; Yannis Papakonstantinou (CoRR, 2017)

Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees. - Etienne Boursier; Jaqueline J. Brito; Chunbin Lin; Yannis Papakonstantinou (CoRR, 2018)

SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits. - Etienne Boursier; Vianney Perchet (NeurIPS, 2019)

Private Learning and Regularized Optimal Transport. - Etienne Boursier; Vianney Perchet (CoRR, 2019)

Utility/Privacy Trade-off through the lens of Optimal Transport. - Etienne Boursier; Vianney Perchet (AISTATS, 2020)

A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players. - Abbas Mehrabian; Etienne Boursier; Emilie Kaufmann; Vianney Perchet (AISTATS, 2020)

Selfish Robustness and Equilibria in Multi-Player Bandits. - Etienne Boursier; Vianney Perchet (COLT, 2020)

Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits. - Pierre Perrault; Etienne Boursier; Michal Valko; Vianney Perchet (NeurIPS, 2020)

Speed of Social Learning from Reviews in Non-Stationary Environments. - Etienne Boursier; Vianney Perchet; Marco Scarsini (CoRR, 2020)

Approximate Analytics System over Compressed Time Series with Tight Deterministic Error Guarantees. - Chunbin Lin; Etienne Boursier; Yannis Papakonstantinou (Proc. VLDB Endow., 2020)

Making the most of your day: online learning for optimal allocation of time. - Etienne Boursier; Tristan Garrec; Vianney Perchet; Marco Scarsini (NeurIPS, 2021)

Decentralized Learning in Online Queuing Systems. - Flore Sentenac; Etienne Boursier; Vianney Perchet (NeurIPS, 2021)

Sequential Learning in a strategical environment. (Apprentissage séquentiel dans un environnement stratégique). - Etienne Boursier (2021)

Social Learning in Non-Stationary Environments. - Etienne Boursier; Vianney Perchet; Marco Scarsini (ALT, 2022)

Trace norm regularization for multi-task learning with scarce data. - Etienne Boursier; Mikhail Konobeev; Nicolas Flammarion (COLT, 2022)

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs. - Etienne Boursier; Loucas Pillaud-Vivien; Nicolas Flammarion (NeurIPS, 2022)

Penalising the biases in norm regularisation enforces sparsity. - Etienne Boursier; Nicolas Flammarion (NeurIPS, 2023)

Model agnostic methods meta-learn despite misspecifications. - Yüksel Oguz; Etienne Boursier; Nicolas Flammarion (CoRR, 2023)

Constant or logarithmic regret in asynchronous multiplayer bandits. - Hugo Richard; Etienne Boursier; Vianney Perchet (CoRR, 2023)

Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication. - Hugo Richard; Etienne Boursier; Vianney Perchet (AISTATS, 2024)

First-order ANIL provably learns representations despite overparametrisation. - Oguz Kaan Yüksel; Etienne Boursier; Nicolas Flammarion (ICLR, 2024)

Incentivized Learning in Principal-Agent Bandit Games. - Antoine Scheid; Daniil Tiapkin; Etienne Boursier; Aymeric Capitaine; Eric Moulines; Michael I. Jordan; El-Mahdi El-Mhamdi; Alain Oliviero Durmus (ICML, 2024)

Unravelling in Collaborative Learning. - Aymeric Capitaine; Etienne Boursier; Antoine Scheid; Eric Moulines; Michael I. Jordan; El-Mahdi El-Mhamdi; Alain Durmus (NeurIPS, 2024)

Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality. - Antoine Scheid; Aymeric Capitaine; Etienne Boursier; Eric Moulines; Michael I. Jordan; Alain Durmus (NeurIPS, 2024)

Early alignment in two-layer networks training is a two-edged sword. - Etienne Boursier; Nicolas Flammarion (CoRR, 2024)

Mitigating Externalities while Learning: an Online Version of the Coase Theorem. - Antoine Scheid; Aymeric Capitaine; Etienne Boursier; Eric Moulines; Michael I. Jordan; Alain Durmus (CoRR, 2024)

Simplicity bias and optimization threshold in two-layer ReLU networks. - Etienne Boursier; Nicolas Flammarion (CoRR, 2024)

Optimal Design for Reward Modeling in RLHF. - Antoine Scheid; Etienne Boursier; Alain Durmus; Michael I. Jordan; Pierre Ménard; Eric Moulines; Michal Valko (CoRR, 2024)

A Survey on Multi-player Bandits. - Etienne Boursier; Vianney Perchet (J. Mach. Learn. Res., 2024)

Utility/privacy trade-off as regularized optimal transport. - Etienne Boursier; Vianney Perchet (Math. Program., 2024)

Approximate information maximization for bandit games. - Alex Barbier-Chebbah; Christian L. Vestergaard; Jean-Baptiste Masson; Etienne Boursier (AISTATS, 2025)

Prediction-Aware Learning in Multi-Agent Systems. - Aymeric Capitaine; Etienne Boursier; Eric Moulines; Michael I. Jordan; Alain Durmus (CoRR, 2025)

Learning Contracts in Hierarchical Multi-Agent Systems. - Antoine Scheid; Etienne Boursier; Alain Durmus; Eric Moulines; Michael I. Jordan (CoRR, 2025)

Online Decision-Focused Learning. - Aymeric Capitaine; Maxime Haddouche; Eric Moulines; Michael I. Jordan; Etienne Boursier; Alain Durmus (CoRR, 2025)

A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation. - Etienne Boursier; Scott Pesme; Radu-Alexandru Dragomir (CoRR, 2025)

Benignity of loss landscape with weight decay requires both large overparametrization and initialization. - Etienne Boursier; Matthew Bowditch; Matthias Englert; Ranko Lazic 001 (CoRR, 2025)