|Time (US Eastern)||Program Item|
|10:00-10:15||Introductions, best paper award: Organizers|
|10:15-10:45||Invited talk: Dinesh Verma, IBM Watson|
|10:45-11:15||Invited talk: Reza Shokri, NUS|
|11:30-12:30||Peer-reviewed paper session #1
[10:45-11:05] 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"
[11:05-11:25] Shuo Liu (Georgetown University), Nirupam Gupta (EPFL), Nitin Vaidya (Georgetown), "Redundancy in cost functions for Byzantine fault-tolerant federated learning"
[11:25-11:45] 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"
|1:30-2:00||Invited talk: Do Le Quoc, Huawei Research|
Panel: FL security: Old wine in new bottle, or NWNB?
Panelists: Salman Avestimehr (USC), Ameet Talwalkar (CMU), Shiva Kasiviswanathan (Amazon), Gerome Bovet (Armasuisse)
|3:00-4:00||Peer-reviewed paper session #2
[3:00-3:20] 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"
[3:20-3:40] 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"
[3:40-4:00] 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”
|4:00-4:30||Invited Talk: Andrea Olgiati, AWS|
|4:30-5:00||Invited Talk: Neil Gong, Duke|
We will have three kinds of activities at the workshop:
Invited talks: We will be inviting leading and emerging thinkers in the field to present at the workshop. There will be no publication associated with these talks, but the talks will be recorded and made available through the workshop website.
Poster papers and presentations at the workshop: Each poster paper will be 2 pages in length (plus references). The poster session will be held using Gather Town which gives the feeling of actually moving about in a physical space and multiple attendees interacting concurrently with the authors. This has been used to good effect in forums like NeurIPS 2020.
Panel: We will have a panel focused on a set of closely related topics within the ambit of the workshop. Examples would be:
After the workshop, we will aggregate a selected group of participants and author an article that serves as a review and a vision of the road ahead. This follows in the line of such an article that has been done on the topic from a ML standpoint["Advances and Open Problems in Federated Learning" Kairouz, McMahan et al., December 2019].