32 citations · 75 across the 13 of their papers we have counts for
18 papers
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems
Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause +1
Contextual Bayesian optimization (CBO) is a powerful framework for sequential decision-making given side information, with important applications, e.g., in wind energy systems. In…
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
Ilija Bogunovic, Zihan Li, Andreas Krause +1
We consider the sequential optimization of an unknown, continuous, and expensive to evaluate reward function, from noisy and adversarially corrupted observed rewards. When the corr…
Misspecified Gaussian Process Bandit Optimization
Ilija Bogunovic, Andreas Krause
We consider the problem of optimizing a black-box function based on noisy bandit feedback. Kernelized bandit algorithms have shown strong empirical and theoretical performance for…
Risk-averse Heteroscedastic Bayesian Optimization
Anastasiia Makarova, Ilnura Usmanova, Ilija Bogunovic +1
Many black-box optimization tasks arising in high-stakes applications require risk-averse decisions. The standard Bayesian optimization (BO) paradigm, however, optimizes the expect…
Contextual Games: Multi-Agent Learning with Side Information
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause +1
We formulate the novel class of contextual games, a type of repeated games driven by contextual information at each round. By means of kernel-based regularity assumptions, we model…
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
In real-world tasks, reinforcement learning (RL) agents frequently encounter situations that are not present during training time. To ensure reliable performance, the RL agents nee…