← Authors

Pierre Gaillard

27 papers · 2012–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (6) 🏃 Academic Marathon (13) 🐝 Cross-Pollinator (14) 🔬 Deep Specialist (12) 🔥 Unstoppable (9) 🗃️ Keyword Collector (104) 💎 Century Club (27) 📈 Trend Setter

Conferences

NIPS (10) ICML (5) AISTATS (4) COLT (4) ALT (3) ICLR (1)

Top co-authors

Aadirupa Saha (5) Margaux Brégère (4) Gilles Stoltz (4) Sébastien Gerchinovitz (3) Nadia Oudjane (3) Rémi Jézéquel (3) Alessandro Rudi (3) Houssam Zenati (3) Olivier Wintenberger (3) Julien Zhou (2)

Keywords

regret bound (16) online learning (11) stochastic optimization (7) multi-armed bandit (6) contextual bandit (3) dueling bandit (3) nonparametric regression (2) adversarial learning (2) sleeping bandit (2) convergence rate (2) stochastic gradient descent (2) mirror descent (2) online algorithm (2) multiclass classification (1) computational efficiency (1) policy optimization (1) covariance estimation (1) ridge regression (1) reinforcement learning (1) preference learning (1)

Papers

Minimax-optimal and Locally-adaptive Online Nonparametric Regression ALT 2025
Online Episodic Convex Reinforcement Learning ICML 2025
Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment ICLR 2025
Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit ALT 2025
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent AISTATS 2024
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NIPS 2024
MetaCURL: Non-stationary Concave Utility Reinforcement Learning NIPS 2024
Sequential Counterfactual Risk Minimization ICML 2023
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits AISTATS 2023
Efficient Kernelized UCB for Contextual Bandits AISTATS 2022
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences ICML 2022
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms NIPS 2021
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits NIPS 2021
Mixability made efficient: Fast online multiclass logistic regression NIPS 2021
Dueling Bandits with Adversarial Sleeping NIPS 2021
Efficient improper learning for online logistic regression COLT 2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model NIPS 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Uniform regret bounds over $\mathbb{R}^d$ for the sequential linear regression problem with the square loss ALT 2019
Efficient online learning with kernels for adversarial large scale problems NIPS 2019
Target Tracking for Contextual Bandits: Application to Demand Side Management ICML 2019
Efficient online algorithms for fast-rate regret bounds under sparsity NIPS 2018
Sparse Accelerated Exponential Weights AISTATS 2017
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning COLT 2017
A Chaining Algorithm for Online Nonparametric Regression COLT 2015
A second-order bound with excess losses COLT 2014
Mirror Descent Meets Fixed Share (and feels no regret) NIPS 2012