← Authors

Michal Valko

101 papers · 2010–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (31) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (15) 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (9) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) 🏠 Conference Loyalist (27) πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (35) πŸ—ƒοΈ Keyword Collector (107) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (13) ⚑ Prolific Year (19) πŸ’Ž Century Club (101)

Conferences

ICML (41) NIPS (27) AISTATS (16) ALT (5) COLT (3) ICLR (3) JMLR (3) ECCV (1) ICCV (1) IJCAI (1)

Top co-authors

RΓ©mi Munos (35) Pierre Menard (22) Daniele Calandriello (21) Alessandro Lazaric (17) Yunhao Tang (17) Mark Rowland (14) Omar Darwiche Domingues (9) Pierre Perrault (9) Jean-Bastien Grill (8) Alexandra Carpentier (8)

Research topics

Statistics (1)

Keywords

regret bound (29) multi-armed bandit (18) online learning (16) sample complexity (14) reinforcement learning (11) markov decision process (10) stochastic optimization (8) online algorithm (6) regret minimization (6) value function (5) upper confidence bound (5) determinantal point process (5) policy optimization (5) self-supervised learning (5) global optimization (4) gaussian process (4) deep reinforcement learning (4) active learning (4) cumulative regret (4) value iteration (3)

Papers

The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback ICML 2025
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving NIPS 2024
Unlocking the Power of Representations in Long-term Novelty-based Exploration ICLR 2024
Demonstration-Regularized RL ICLR 2024
A General Theoretical Paradigm to Understand Learning from Human Preferences AISTATS 2024
Generalized Preference Optimization: A Unified Approach to Offline Alignment ICML 2024
Nash Learning from Human Feedback ICML 2024
Decoding-time Realignment of Language Models ICML 2024
Human Alignment of Large Language Models through Online Preference Optimisation ICML 2024
Local and Adaptive Mirror Descents in Extensive-Form Games NIPS 2024
Quantile Credit Assignment ICML 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm ICML 2023
VA-learning as a more efficient alternative to Q-learning ICML 2023
Fast Rates for Maximum Entropy Exploration ICML 2023
Model-free Posterior Sampling via Learning Rate Randomization NIPS 2023
Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023
Adapting to game trees in zero-sum imperfect information games ICML 2023
Half-Hop: A graph upsampling approach for slowing down message passing ICML 2023
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments ICML 2023
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NIPS 2022
Large-Scale Representation Learning on Graphs via Bootstrapping ICLR 2022
BYOL-Explore: Exploration by Bootstrapped Prediction NIPS 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses ICML 2022
Retrieval-Augmented Reinforcement Learning ICML 2022
Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times ICML 2022
Marginalized Operators for Off-policy Reinforcement Learning AISTATS 2022
Adaptive Multi-Goal Exploration AISTATS 2022
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation NIPS 2021
Broaden Your Views for Self-Supervised Video Learning ICCV 2021
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited ALT 2021
Revisiting Peng’s Q($Ξ»$) for Modern Reinforcement Learning ICML 2021
Taylor Expansion of Discount Factors ICML 2021
UCB Momentum Q-learning: Correcting the bias without forgetting ICML 2021
Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021
Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model ALT 2021
Adaptive Reward-Free Exploration ALT 2021
Online A-Optimal Design and Active Linear Regression ICML 2021
Fast active learning for pure exploration in reinforcement learning ICML 2021
Learning in two-player zero-sum partially observable Markov games with perfect recall NIPS 2021
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity NIPS 2021
A Provably Efficient Sample Collection Strategy for Reinforcement Learning NIPS 2021
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret NIPS 2021
A single algorithm for both restless and rested rotting bandits AISTATS 2020
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity NIPS 2020
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits NIPS 2020
Sampling from a k-DPP without looking at all items NIPS 2020
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs NIPS 2020
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning NIPS 2020
Fixed-confidence guarantees for Bayesian best-arm identification AISTATS 2020
Derivative-Free & Order-Robust Optimisation AISTATS 2020
Adaptive multi-fidelity optimization with fast learning rates AISTATS 2020
Covariance-adapting algorithm for semi-bandits with application to sparse outcomes COLT 2020
Near-linear time Gaussian process optimization with adaptive batching and resparsification ICML 2020
Gamification of Pure Exploration for Linear Bandits ICML 2020
Stochastic bandits with arm-dependent delays ICML 2020
Monte-Carlo Tree Search as Regularized Policy Optimization ICML 2020
Budgeted Online Influence Maximization ICML 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Taylor Expansion Policy Optimization ICML 2020
No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020
Spectral bandits JMLR 2020
Active multiple matrix completion with adaptive confidence sets AISTATS 2019
Exploiting structure of uncertainty for efficient matroid semi-bandits ICML 2019
Scale-free adaptive planning for deterministic dynamics & discounted rewards ICML 2019
Exact sampling of determinantal point processes with sublinear time preprocessing NIPS 2019
A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption ALT 2019
Multiagent Evaluation under Incomplete Information NIPS 2019
Rotting bandits are no harder than stochastic ones AISTATS 2019
Finding the bandit in a graph: Sequential search-and-stop AISTATS 2019
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret COLT 2019
On two ways to use determinantal point processes for Monte Carlo integration NIPS 2019
Planning in entropy-regularized Markov decision processes and games NIPS 2019
DPPy: DPP Sampling with Python JMLR 2019
General parallel optimization a without metric ALT 2019
Improved large-scale graph learning through ridge spectral sparsification ICML 2018
Best of both worlds: Stochastic & adversarial best-arm identification COLT 2018
Compressing the Input for CNNs with the First-Order Scattering Transform ECCV 2018
Optimistic optimization of a Brownian NIPS 2018
Zonotope Hit-and-run for Efficient Sampling from Projection DPPs ICML 2017
Efficient Second-Order Online Kernel Learning with Adaptive Embedding NIPS 2017
Distributed Adaptive Sampling for Kernel Matrix Approximation AISTATS 2017
Trading off Rewards and Errors in Multi-Armed Bandits AISTATS 2017
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback NIPS 2017
Second-Order Kernel Online Convex Optimization with Adaptive Sketching ICML 2017
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning NIPS 2016
Online Learning with Noisy Side Observations AISTATS 2016
Bayesian Policy Gradient and Actor-Critic Algorithms JMLR 2016
Revealing Graph Bandits for Maximizing Local Influence AISTATS 2016
Pliable Rejection Sampling ICML 2016
Black-box optimization of noisy functions with unknown smoothness NIPS 2015
Maximum Entropy Semi-Supervised Inverse Reinforcement Learning IJCAI 2015
Simple regret for infinitely many armed bandits ICML 2015
Cheap Bandits ICML 2015
Spectral Bandits for Smooth Graph Functions ICML 2014
Online combinatorial optimization with stochastic decision sets and adversarial losses NIPS 2014
Extreme bandits NIPS 2014
Efficient learning by implicit exploration in bandit problems with side observations NIPS 2014
Stochastic Simultaneous Optimistic Optimization ICML 2013
Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010