133 citations · 803 across the 68 of their papers we have counts for
9 papers · 1 filter
Simple Coding Techniques for Many-Hop Relaying
Yan Hao Ling, Jonathan Scarlett
In this paper, we study the problem of relaying a single bit of information across a series of binary symmetric channels, and the associated trade-off between the number of hops $m…
Adversarial Attacks on Gaussian Process Bandits
Eric Han, Jonathan Scarlett
Gaussian processes (GP) are a widely-adopted tool used to sequentially optimize black-box functions, where evaluations are costly and potentially noisy. Recent works on GP bandits…
Gaussian Process Bandit Optimization with Few Batches
Zihan Li, Jonathan Scarlett
In this paper, we consider the problem of black-box optimization using Gaussian Process (GP) bandit optimization with a small number of batches. Assuming the unknown function has a…
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…
Noisy Adaptive Group Testing via Noisy Binary Search
Bernard Teo, Jonathan Scarlett
The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and has numerous practical ap…
Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing
Eric Price, Jonathan Scarlett, Nelvin Tan
In group testing, the goal is to identify a subset of defective items within a larger set of items based on tests whose outcomes indicate whether at least one defective item is pre…
Optimal Rates of Teaching and Learning Under Uncertainty
Yan Hao Ling, Jonathan Scarlett
In this paper, we consider a recently-proposed model of teaching and learning under uncertainty, in which a teacher receives independent observations of a single bit corrupted by b…
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".…