2 citations · 3 across the 3 of their papers we have counts for
4 papers
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…
Generalized Geometric Programming for Rate Allocation in Consensus
Ryan Pilgrim, Junan Zhu, Dror Baron +1
Distributed averaging, or distributed average consensus, is a common method for computing the sample mean of the data dispersed among the nodes of a network in a decentralized mann…
Source Coding Optimization for Distributed Average Consensus
Ryan Pilgrim
Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nod…
An Overview of Multi-Processor Approximate Message Passing
Junan Zhu, Ryan Pilgrim, Dror Baron
Approximate message passing (AMP) is an algorithmic framework for solving linear inverse problems from noisy measurements, with exciting applications such as reconstructing images,…