research
∙
02/08/2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning
A practical challenge in reinforcement learning are combinatorial action...
share
research
∙
02/07/2023
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications
Partial monitoring is an expressive framework for sequential decision-ma...
research
∙
03/26/2022
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization
Tuning machine parameters of particle accelerators is a repetitive and t...
research
∙
05/25/2021
Bias-Robust Bayesian Optimization via Dueling Bandit
We consider Bayesian optimization in settings where observations can be ...
research
∙
01/21/2021
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
Combinatorial bandits with semi-bandit feedback generalize multi-armed b...
research
∙
11/11/2020
Asymptotically Optimal Information-Directed Sampling
We introduce a computationally efficient algorithm for finite stochastic...
research
∙
02/25/2020
Information Directed Sampling for Linear Partial Monitoring
Partial monitoring is a rich framework for sequential decision making un...
research
∙
02/20/2020
Distributionally Robust Bayesian Optimization
Robustness to distributional shift is one of the key challenges of conte...
research
∙
06/06/2019
Stochastic Bandits with Context Distributions
We introduce a novel stochastic contextual bandit model, where at each s...
research
∙
02/08/2019
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
Bayesian optimization is known to be difficult to scale to high dimensio...
research
∙
12/18/2018
Information-Directed Exploration for Deep Reinforcement Learning
Efficient exploration remains a major challenge for reinforcement learni...
research
∙
01/29/2018
