32 citations · 56 across the 10 of their papers we have counts for
27 papers
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…
Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals
Sidhant Bansal, Arnab Bhattacharyya, Anamay Chaturvedi +1
A {\em universal 1-bit compressive sensing (CS)} scheme consists of a measurement matrix such that all signals belonging to a particular class can be approximately recovere…
Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors
Zhaoqiang Liu, Subhroshekhar Ghosh, Jun Han +1
In 1-bit compressive sensing, each measurement is quantized to a single bit, namely the sign of a linear function of an unknown vector, and the goal is to accurately recover the ve…
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…