Richeng Jin | DeepAI

DeepAI AI Chat

Featured Co-authors

Zhaoyang Zhang
81 publications
Zhaohui Yang
77 publications
Huaiyu Dai
58 publications
Tianfu Wu
48 publications
Caijun Zhong
40 publications
Shih-Chun Lin
16 publications
Dror Baron
14 publications
Xiaofan He
11 publications
Chau-Wai Wong
10 publications
Md Ferdous Pervej
9 publications
Yufan Huang
7 publications

∙ 08/03/2023

Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity

While a practical wireless network has many tiers where end users do not...

0 Md Ferdous Pervej, et al. ∙

∙ 05/22/2023

Distributed Learning over Networks with Graph-Attention-Based Personalization

In conventional distributed learning over a network, multiple agents col...

0 Zhuojun Tian, et al. ∙

∙ 02/19/2023

Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity

Communication overhead has become one of the major bottlenecks in the di...

0 Richeng Jin, et al. ∙

∙ 02/19/2023

On the f-Differential Privacy Guarantees of Discrete-Valued Mechanisms

We consider a federated data analytics problem in which a server coordin...

0 Richeng Jin, et al. ∙

∙ 10/27/2022

Resource Constrained Vehicular Edge Federated Learning with Highly Mobile Connected Vehicles

This paper proposes a vehicular edge federated learning (VEFL) solution,...

0 Md Ferdous Pervej, et al. ∙

∙ 06/08/2022

Gradient Obfuscation Gives a False Sense of Security in Federated Learning

Federated learning has been proposed as a privacy-preserving machine lea...

0 Kai Yue, et al. ∙

∙ 02/15/2022

Efficient Content Delivery in Cache-Enabled VEN with Deadline-Constrained Heterogeneous Demands: A User-Centric Approach

Modern connected vehicles (CVs) frequently require diverse types of cont...

0 Md Ferdous Pervej, et al. ∙

∙ 10/07/2021

Neural Tangent Kernel Empowered Federated Learning

Federated learning (FL) is a privacy-preserving paradigm where multiple ...

6 Kai Yue, et al. ∙

∙ 10/06/2021

Federated Learning via Plurality Vote

Federated learning allows collaborative workers to solve a machine learn...

0 Kai Yue, et al. ∙

∙ 08/02/2021

Communication-Efficient Federated Learning via Predictive Coding

Federated learning can enable remote workers to collaboratively train a ...

0 Kai Yue, et al. ∙

∙ 04/15/2020

On the Design of Communication Efficient Federated Learning over Wireless Networks

Recently, federated learning (FL), as a promising distributed machine le...

0 Richeng Jin, et al. ∙

∙ 02/25/2020

Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Federated learning (FL) has emerged as a prominent distributed learning ...

17 Richeng Jin, et al. ∙

∙ 02/27/2019

Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data

The recent advances in sensor technologies and smart devices enable the ...

0 Richeng Jin, et al. ∙

∙ 09/08/2018

Decentralized Differentially Private Without-Replacement Stochastic Gradient Descent

While machine learning has achieved remarkable results in a wide variety...

0 Richeng Jin, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world