32 citations · 57 across the 12 of their papers we have counts for
11 papers · 1 filter
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…
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors
Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett
Compressive phase retrieval is a popular variant of the standard compressive sensing problem in which the measurements only contain magnitude information. In this paper, motivated…
Lenient Regret and Good-Action Identification in Gaussian Process Bandits
Xu Cai, Selwyn Gomes, Jonathan Scarlett
In this paper, we study the problem of Gaussian process (GP) bandits under relaxed optimization criteria stating that any function value above a certain threshold is "good enough".…
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…
The Generalized Lasso with Nonlinear Observations and Generative Priors
Zhaoqiang Liu, Jonathan Scarlett
In this paper, we study the problem of signal estimation from noisy non-linear measurements when the unknown -dimensional signal is in the range of an -Lipschitz continuous g…
Corruption-Tolerant Gaussian Process Bandit Optimization
Ilija Bogunovic, Andreas Krause, Jonathan Scarlett
We consider the problem of optimizing an unknown (typically non-convex) function with a bounded norm in some Reproducing Kernel Hilbert Space (RKHS), based on noisy bandit feedback…