31 citations · 167 across the 30 of their papers we have counts for
11 papers · 1 filter
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…
Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause
We consider Bayesian optimization in settings where observations can be adversarially biased, for example by an uncontrolled hidden confounder. Our first contribution is a reductio…
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
Marc Jourdan, Mojmír Mutný, Johannes Kirschner +1
Combinatorial bandits with semi-bandit feedback generalize multi-armed bandits, where the agent chooses sets of arms and observes a noisy reward for each arm contained in the chose…
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator
Max B. Paulus, Chris J. Maddison, Andreas Krause
Gradient estimation in models with discrete latent variables is a challenging problem, because the simplest unbiased estimators tend to have high variance. To counteract this, mode…
Stochastic Linear Bandits Robust to Adversarial Attacks
Ilija Bogunovic, Arpan Losalka, Andreas Krause +1
We consider a stochastic linear bandit problem in which the rewards are not only subject to random noise, but also adversarial attacks subject to a suitable budget (i.e., an up…