52 citations · 72 across the 6 of their papers we have counts for
6 papers · 1 filter
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
Mohamed Seif, Wei-Ting Chang, Ravi Tandon
In this paper, we study the problem of federated learning over a wireless channel with user sampling, modeled by a Gaussian multiple access channel, subject to central and local di…
Communication Efficient Federated Learning over Multiple Access Channels
Wei-Ting Chang, Ravi Tandon
In this work, we study the problem of federated learning (FL), where distributed users aim to jointly train a machine learning model with the help of a parameter server (PS). In ea…
Cache-Aided Content Delivery in Fog-RAN Systems with Topological Information and no CSI
Wei-Ting Chang, Ravi Tandon, Osvaldo Simeone
In this work, we consider a Fog Radio Access Network (F-RAN) system with a partially connected wireless topology and no channel state information available at the cloud and Edge No…
On the Upload versus Download Cost for Secure and Private Matrix Multiplication
Wei-Ting Chang, Ravi Tandon
In this paper, we study the problem of secure and private distributed matrix multiplication. Specifically, we focus on a scenario where a user wants to compute the product of a con…
Random Sampling for Distributed Coded Matrix Multiplication
Wei-Ting Chang, Ravi Tandon
Matrix multiplication is a fundamental building block for large scale computations arising in various applications, including machine learning. There has been significant recent in…
On the Capacity of Secure Distributed Matrix Multiplication
Wei-Ting Chang, Ravi Tandon
Matrix multiplication is one of the key operations in various engineering applications. Outsourcing large-scale matrix multiplication tasks to multiple distributed servers or cloud…