activity
20142024
most citedFundamental Limits of Caching in Wireless D2D Networks

12 citations · 15 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2024

A New Theoretical Perspective on Data Heterogeneity in Federated Optimization

Jiayi Wang, Shiqiang Wang, Rong-Rong Chen +1

In federated learning (FL), data heterogeneity is the main reason that existing theoretical analyses are pessimistic about the convergence rate. In particular, for many FL algorith…

cs.IT2024

Decentralized Uncoded Storage Elastic Computing with Heterogeneous Computation Speeds

Wenbo Huang, Xudong You, Kai Wan +2

Elasticity plays an important role in modern cloud computing systems. Elastic computing allows virtual machines (i.e., computing nodes) to be preempted when high-priority jobs aris…

cs.NI2024

SPARC-LoRa: A Scalable, Power-efficient, Affordable, Reliable, and Cloud Service-enabled LoRa Networking System for Agriculture Applications

Xi Wang, Bryan Hatasaka, Zhengyan Liu +10

With the rapid development of cloud and edge computing, Internet of Things (IoT) applications have been deployed in various aspects of human life. In this paper, we design and impl…

cs.IT2024

Uncoded Storage Coded Transmission Elastic Computing with Straggler Tolerance in Heterogeneous Systems

Xi Zhong, Joerg Kliewer, Mingyue Ji

In 2018, Yang et al. introduced a novel and effective approach, using maximum distance separable (MDS) codes, to mitigate the impact of elasticity in cloud computing systems. This…

cs.IT2024

Physics-informed Generalizable Wireless Channel Modeling with Segmentation and Deep Learning: Fundamentals, Methodologies, and Challenges

Ethan Zhu, Haijian Sun, Mingyue Ji

Channel modeling is fundamental in advancing wireless systems and has thus attracted considerable research focus. Recent trends have seen a growing reliance on data-driven techniqu…

cs.IT2023

The Capacity Region of Information Theoretic Secure Aggregation with Uncoded Groupwise Keys

Kai Wan, Hua Sun, Mingyue Ji +2

This paper considers the secure aggregation problem for federated learning under an information theoretic cryptographic formulation, where distributed training nodes (referred to a…