Workshop on Systems Challenges in Reliable and Secure Federated Learning

Co-located with ACM SOSP 2021

October 25, 2021

In Virtual Land

Accepted Papers

1. Fan Lai (University of Michigan), Yinwei Dai (University of Michigan), Xiangfeng Zhu (University of Michigan), Harsha V. Madhyastha (University of Michigan), Mosharaf Chowdhury (University of Michigan), "FedScale: Benchmarking Model and System Performance of Federated Learning"

2. Shuo Liu (Georgetown University), Nirupam Gupta (EPFL), Nitin Vaidya (Georgetown), "Redundancy in cost functions for Byzantine fault-tolerant federated learning"

3. Kunlong Liu (University of California, Santa Barbara), Richa Wadaskar (University of California, Santa Barbara), Trinabh Gupta (University of California, Santa Barbara), "Towards an Efficient System for Differentially-private, Cross-device Federated Learning"

4. Aghiles Ait Messaoud (ESI, Algeria), Vlad Nitu (INSA Lyon), Valerio Schiavoni (University of Neuchatel, Switzerland), Sonia Ben Mokhtar (LIRIS-CNRS, France), "GradSec: a TEE-based Scheme Against Federated Learning Inference Attacks"

5. Harikrishna Kuttivelil (University of California, Santa Cruz, CA (UCSC)), Katia Obraczka (University of California, Santa Cruz, CA (UCSC)), "Community-Structured Decentralized Learning for Resilient EI"

6. Pau-Chen Cheng (IBM Research), Kevin Eykholt (IBM Research), Zhongshu Gu (IBM Research), Hani Jamjoom (IBM Research), K. R. Jayaram (IBM Research), Enriquillo Valdez (IBM Research), Ashish Verma (IBM Research), "Separation of Powers in Federated Learning"