Gergely Neu
46 papers · 2010–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (14) π Conference Polyglot (7)
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Taxonomy Completionist
(14)
π§
Keyword Pioneer
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Keyword Champion
(4)
π¬
Deep Specialist
(14)
ποΈ
Keyword Collector
(136)
π
Conference Pioneer
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Trend Setter
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Century Club
(46)
π₯
Unstoppable
(14)
β‘
Prolific Year
(6)
Conferences
NIPS (15)
COLT (12)
AISTATS (7)
ALT (7)
ICML (3)
JMLR (1)
L4DC (1)
Top co-authors
Research topics
Keywords
regret bound
(19)
online learning
(14)
contextual bandit
(6)
combinatorial optimization
(6)
markov decision process
(6)
regret minimization
(5)
multi-armed bandit
(5)
bandit feedback
(4)
markov decision processes
(3)
reinforcement learning
(3)
stochastic gradient descent
(3)
linear function approximation
(3)
adversarial learning
(3)
relative entropy policy search
(2)
policy optimization
(2)
expert advice
(2)
bandit setting
(2)
learning theory
(2)
online prediction
(2)
dynamic programming
(2)
Papers
Offline RL via Feature-Occupancy Gradient Ascent
AISTATS 2025
Online-to-PAC generalization bounds under graph-mixing dependencies
AISTATS 2025
Generalization bounds for mixing processes via delayed online-to-PAC conversions
ALT 2025
Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
COLT 2025
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
NIPS 2024
Offline Primal-Dual Reinforcement Learning for Linear MDPs
AISTATS 2024
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
ICML 2024
Importance-Weighted Offline Learning Done Right
ALT 2024
Adversarial Contextual Bandits Go Kernelized
ALT 2024
Optimistic Information Directed Sampling
COLT 2024
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization
ALT 2023
Optimistic Planning by Regularized Dynamic Programming
ICML 2023
Online Learning with Off-Policy Feedback
ALT 2023
Conference on Learning Theory 2023: Preface
COLT 2023
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
NIPS 2023
Nonstochastic Contextual Combinatorial Bandits
AISTATS 2023
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits
NIPS 2022
Generalization Bounds via Convex Analysis
COLT 2022
Proximal Point Imitation Learning
NIPS 2022
Logistic Q-Learning
AISTATS 2021
Online learning in MDPs with linear function approximation and bandit feedback.
NIPS 2021
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent
COLT 2021
Faster saddle-point optimization for solving large-scale Markov decision processes
L4DC 2020
A Unifying View of Optimism in Episodic Reinforcement Learning
NIPS 2020
Algorithmic Learning Theory 2020: Preface
ALT 2020
Fast Rates for Online Prediction with Abstention
COLT 2020
Efficient and robust algorithms for adversarial linear contextual bandits
COLT 2020
Bandit Principal Component Analysis
COLT 2019
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates
NIPS 2019
Beating SGD Saturation with Tail-Averaging and Minibatching
NIPS 2019
Online Influence Maximization with Local Observations
ALT 2019
Iterate Averaging as Regularization for Stochastic Gradient Descent
COLT 2018
Fast rates for online learning in Linearly Solvable Markov Decision Processes
COLT 2017
Algorithmic Stability and Hypothesis Complexity
ICML 2017
Boltzmann Exploration Done Right
NIPS 2017
Online Learning with Noisy Side Observations
AISTATS 2016
Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits
JMLR 2016
Explore no more: Improved high-probability regret bounds for non-stochastic bandits
NIPS 2015
First-order regret bounds for combinatorial semi-bandits
COLT 2015
Efficient learning by implicit exploration in bandit problems with side observations
NIPS 2014
Exploiting easy data in online optimization
NIPS 2014
Online combinatorial optimization with stochastic decision sets and adversarial losses
NIPS 2014
Online learning in episodic Markovian decision processes by relative entropy policy search
NIPS 2013
Prediction by random-walk perturbation
COLT 2013
The adversarial stochastic shortest path problem with unknown transition probabilities
AISTATS 2012
Online Markov Decision Processes under Bandit Feedback
NIPS 2010