I. Bogunovic

Latest

• Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
• Adversarial Robust Decision Transformer: Enhancing Robustness of RvS via Minimax Returns-to-go
• Group Robust Preference Optimization in Reward-free RLHF
• REDUCR: Robust Data Downsampling Using Class Priority Reweighting
• Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration
• Robust Best-arm Identification in Linear Bandits
• Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
• Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning
• Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning
• Near-optimal Policy Identification in Active Reinforcement Learning
• Movement Penalized Bayesian Optimization with Application to Wind Energy Systems
• Graph Neural Network Bandits
• A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
• Misspecified Gaussian Process Bandit Optimization
• Risk-averse Heteroscedastic Bayesian Optimization
• Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning
• Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
• Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
• DP-Sniper: Black-Box Discovery of Differential Privacy Violations using Classifiers
• Stochastic Linear Bandits Robust to Adversarial Attacks
• Contextual Games: Multi-Agent Learning with Side Information
• Learning to Play Sequential Games versus Unknown Opponents
• Corruption-Tolerant Gaussian Process Bandit Optimization
• Mixed Strategies for Robust Optimization of Unknown Objectives
• Distributionally Robust Bayesian Optimization
• No-Regret Learning in Unknown Games with Correlated Payoffs
• Overlapping Multi-Bandit Best Arm Identification
• Robust Adaptive Decision Making: Bayesian Optimization and Beyond
• Adversarially Robust Optimization with Gaussian Processes
• High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
• Robust Maximization of Non-Submodular Objectives
• A Distributed Algorithm for Partitioned Robust Submodular Maximization
• Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach
• Robust Submodular Maximization: A Non-Uniform Partitioning Approach
• Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
• An Efficient Streaming Algorithm for the Submodular Cover Problem
• Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
• Time-Varying Gaussian Process Bandit Optimization
• Learning-Based Compressive Subsampling
• Active Learning of Self-concordant like Multi-index Functions
• Near-Optimally Teaching the Crowd to Classify