activity
20192026
most citedTowards Personalized Federated Learning

1.2k citations · 1.8k across the 28 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.CR2020★ 47 cited

Privacy and Robustness in Federated Learning: Attacks and Defenses

Lingjuan Lyu, Han Yu, Xingjun Ma +5

As data are increasingly being stored in different silos and societies becoming more aware of data privacy issues, the traditional centralized training of artificial intelligence (…

cs.CR2020★ 2 cited

SCNet: A Neural Network for Automated Side-Channel Attack

Guanlin Li, Chang Liu, Han Yu +4

The side-channel attack is an attack method based on the information gained about implementations of computer systems, rather than weaknesses in algorithms. Information about syste…

cs.GT2020★ 4 cited

Optimal Procurement Auction for Cooperative Production of Virtual Products: Vickrey-Clarke-Groves Meet Cremer-McLean

Mingshu Cong, Xi Weng, Han Yu +2

We set up a supply-side game-theoretic model for the cooperative production of virtual products. In our model, a group of producers collaboratively produce a virtual product by con…

cs.LG2020★ 29 cited

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention

Ce Ju, Ruihui Zhao, Jichao Sun +11

Prevention of stroke with its associated risk factors has been one of the public health priorities worldwide. Emerging artificial intelligence technology is being increasingly adop…

cs.CR2020★ 237 cited

Threats to Federated Learning: A Survey

Lingjuan Lyu, Han Yu, Qiang Yang

With the emergence of data silos and popular privacy awareness, the traditional centralized approach of training artificial intelligence (AI) models is facing strong challenges. Fe…

cs.CR2020★ 21 cited

FedCoin: A Peer-to-Peer Payment System for Federated Learning

Yuan Liu, Shuai Sun, Zhengpeng Ai +3

Federated learning (FL) is an emerging collaborative machine learning method to train models on distributed datasets with privacy concerns. To properly incentivize data owners to c…

cs.LG2020★ 39 cited

FOCUS: Dealing with Label Quality Disparity in Federated Learning

Yiqiang Chen, Xiaodong Yang, Xin Qin +3

Ubiquitous systems with End-Edge-Cloud architecture are increasingly being used in healthcare applications. Federated Learning (FL) is highly useful for such applications, due to s…