133 citations · 803 across the 68 of their papers we have counts for
8 papers · 1 filter
An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing
Jonathan Scarlett
In this paper, we consider the group testing problem with adaptive test designs and noisy outcomes. We propose a computationally efficient four-stage procedure with components incl…
A Characteristic Function Approach to Deep Implicit Generative Modeling
Abdul Fatir Ansari, Jonathan Scarlett, Harold Soh
Implicit Generative Models (IGMs) such as GANs have emerged as effective data-driven models for generating samples, particularly images. In this paper, we formulate the problem of…
Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models
Zhaoqiang Liu, Jonathan Scarlett
It has recently been shown that for compressive sensing, significantly fewer measurements may be required if the sparsity assumption is replaced by the assumption the unknown vecto…
Learning Erdős-Rényi Random Graphs via Edge Detecting Queries
Zihan Li, Matthias Fresacher, Jonathan Scarlett
In this paper, we consider the problem of learning an unknown graph via queries on groups of nodes, with the result indicating whether or not at least one edge is present among tho…
Sublinear-Time Non-Adaptive Group Testing with Tests via Bit-Mixing Coding
Steffen Bondorf, Binbin Chen, Jonathan Scarlett +2
The group testing problem consists of determining a small set of defective items from a larger set of items based on tests on groups of items, and is relevant in applications such…
Group Testing: An Information Theory Perspective
Matthew Aldridge, Oliver Johnson, Jonathan Scarlett
The group testing problem concerns discovering a small number of defective items within a large population by performing tests on pools of items. A test is positive if the pool con…
Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limits
Lan V. Truong, Jonathan Scarlett
The support recovery problem consists of determining a sparse subset of variables that is relevant in generating a set of observations. In this paper, we study the support recovery…
An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation
Jonathan Scarlett, Volkan Cevher
Information theory plays an indispensable role in the development of algorithm-independent impossibility results, both for communication problems and for seemingly distinct areas s…