Pierre Gaillard
29 papers · 2012–2026 · 6 conferences · across top CS/AI conferences
Achievements
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🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (11) 🌍 Conference Polyglot (6)
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Academic Marathon
(13)
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(14)
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(12)
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(9)
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(27)
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Conferences
NIPS (10)
ALT (5)
ICML (5)
AISTATS (4)
COLT (4)
ICLR (1)
Top co-authors
Keywords
regret bound
(17)
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
Online Markov Decision Processes with Terminal Law Constraints
ALT 2026
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
ALT 2026
Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
ALT 2025
Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment
ICLR 2025
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
ALT 2025
Online Episodic Convex Reinforcement Learning
ICML 2025
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
NIPS 2024
MetaCURL: Non-stationary Concave Utility Reinforcement Learning
NIPS 2024
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent
AISTATS 2024
Sequential Counterfactual Risk Minimization
ICML 2023
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits
AISTATS 2023
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
ICML 2022
Efficient Kernelized UCB for Contextual Bandits
AISTATS 2022
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
NIPS 2021
Mixability made efficient: Fast online multiclass logistic regression
NIPS 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
NIPS 2021
Dueling Bandits with Adversarial Sleeping
NIPS 2021
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards
ICML 2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
NIPS 2020
Efficient improper learning for online logistic regression
COLT 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
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
COLT 2017
Sparse Accelerated Exponential Weights
AISTATS 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