activity
20202026
most citedFedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System

37 citations · 69 across the 20 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.IT2023

Capacity of Summation over a Symmetric Quantum Erasure MAC with Partially Replicated Inputs

Yuhang Yao, Syed A. Jafar

The optimal quantum communication cost of computing a classical sum of distributed sources is studied over a quantum erasure multiple access channel (QEMAC). K classical messages c…

cs.IT2023★ 7 cited

On the Capacity of Secure -user Product Computation over a Quantum MAC

Yuxiang Lu, Yuhang Yao, Syed A. Jafar

Inspired by recent work by Christensen and Popovski on secure -user product computation for finite-fields of prime-order over a quantum multiple access channel, the generalizati…

cs.IT2023★ 10 cited

The Capacity of Classical Summation over a Quantum MAC with Arbitrarily Distributed Inputs and Entanglements

Yuhang Yao, Syed A. Jafar

The -QMAC problem is introduced, involving servers, classical () data streams, and independent quantum systems. Data stream is rep…

cs.IT2023

-Sum Box: An Abstraction for Linear Computation over Many-to-one Quantum Networks

Matteo Allaix, Yuxiang Lu, Yuhang Yao +3

Linear computations over quantum many-to-one communication networks offer opportunities for communication cost improvements through schemes that exploit quantum entanglement among…

cs.LG2023★ 37 cited

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System

Weizhao Jin, Yuhang Yao, Shanshan Han +5

Federated Learning trains machine learning models on distributed devices by aggregating local model updates instead of local data. However, privacy concerns arise as the aggregated…