93 citations · 524 across the 46 of their papers we have counts for
47 papers
Group Testing with Side Information via Generalized Approximate Message Passing
Shu-Jie Cao, Ritesh Goenka, Chau-Wai Wong +2
Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In a group testing setup, we are given n samples, one per individual. Each indiv…
Mismatched Estimation in the Distance Geometry Problem
Mahmoud Abdelkhalek, Dror Baron, Chau-Wai Wong
We investigate mismatched estimation in the context of the distance geometry problem (DGP). In the DGP, for a set of points, we are given noisy measurements of pairwise distances b…
Gradient Obfuscation Gives a False Sense of Security in Federated Learning
Kai Yue, Richeng Jin, Chau-Wai Wong +2
Federated learning has been proposed as a privacy-preserving machine learning framework that enables multiple clients to collaborate without sharing raw data. However, client priva…
Neural Tangent Kernel Empowered Federated Learning
Kai Yue, Richeng Jin, Ryan Pilgrim +3
Federated learning (FL) is a privacy-preserving paradigm where multiple participants jointly solve a machine learning problem without sharing raw data. Unlike traditional distribut…
Contact Tracing Information Improves the Performance of Group Testing Algorithms
Ritesh Goenka, Shu-Jie Cao, Chau-Wai Wong +2
Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In group testing, we are given samples, one per individual. These samples ar…
Contact Tracing Enhances the Efficiency of COVID-19 Group Testing
Ritesh Goenka, Shu-Jie Cao, Chau-Wai Wong +2
Group testing can save testing resources in the context of the ongoing COVID-19 pandemic. In group testing, we are given samples, one per individual, and arrange them into $m <…