András György

Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits AISTATS 2025 Learning Continually by Spectral Regularization ICLR 2025 Toward Understanding In-context vs. In-weight Learning ICLR 2025 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NIPS 2024 To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty NIPS 2024 Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL NIPS 2023 Optimistic Meta-Gradients NIPS 2023 Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore NIPS 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023 Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost ICML 2023 A Second-Order Method for Stochastic Bandit Convex Optimisation COLT 2023 A New Look at Dynamic Regret for Non-Stationary Stochastic Bandits JMLR 2023 Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning AISTATS 2022 Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs NIPS 2022 TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions ALT 2022 On the Role of Neural Collapse in Transfer Learning ICLR 2022 Defending Against Image Corruptions Through Adversarial Augmentations ICLR 2022 Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling JMLR 2022 Adapting to Delays and Data in Adversarial Multi-Armed Bandits ICML 2021 Improved Regret for Zeroth-Order Stochastic Convex Bandits COLT 2021 Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting AISTATS 2021 Mirror Descent and the Information Ratio COLT 2021 A FRAMEWORK FOR ROBUSTNESS CERTIFICATION OF SMOOTHED CLASSIFIERS USING F-DIVERGENCES ICLR 2020 ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool NIPS 2020 Non-Stationary Delayed Bandits with Intermediate Observations ICML 2020 A simpler approach to accelerated optimization: iterative averaging meets optimism ICML 2020 Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems ICML 2019 CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration ICML 2019 Detecting Overfitting via Adversarial Examples NIPS 2019 Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging NIPS 2019 Adaptive MCMC via Combining Local Samplers AISTATS 2019 LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration ICML 2018 Following the Leader and Fast Rates in Online Linear Prediction: Curved Constraint Sets and Other Regularities JMLR 2017 A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds ALT 2017 Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities NIPS 2016 Shifting Regret, Mirror Descent, and Matrices ICML 2016 (Bandit) Convex Optimization with Biased Noisy Gradient Oracles AISTATS 2016 SDP Relaxation with Randomized Rounding for Energy Disaggregation NIPS 2016 Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM AISTATS 2015 On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments ICML 2015 Deterministic Independent Component Analysis ICML 2015 Online Learning with Gaussian Payoffs and Side Observations NIPS 2015 Fast Cross-Validation for Incremental Learning IJCAI 2015 Near-optimal max-affine estimators for convex regression AISTATS 2015 Online Learning in Markov Decision Processes with Changing Cost Sequences ICML 2014 Adaptive Monte Carlo via Bandit Allocation ICML 2014 A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning ICML 2013 Online Learning with Costly Features and Labels NIPS 2013 Online Learning under Delayed Feedback ICML 2013 The adversarial stochastic shortest path problem with unknown transition probabilities AISTATS 2012 A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping AISTATS 2010 On-Line Sequential Bin Packing JMLR 2010 Online Markov Decision Processes under Bandit Feedback NIPS 2010 The On-Line Shortest Path Problem Under Partial Monitoring JMLR 2007