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Workshop: International Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020)

Xiaolin Andy Li, Dejing Dou, Ameet Talwalkar, Hongyu Li, Jianzong Wang, Yanzhi Wang

2020-12-12T08:20:00-08:00 - 2020-12-12T19:10:00-08:00
Abstract: In the recent decade, we have witnessed rapid progress in machine learning in general and deep learning in particular, mostly driven by tremendous data. As these intelligent algorithms, systems, and applications are deployed in real-world scenarios, we are now facing new challenges, such as scalability, security, privacy, trust, cost, regulation, and environmental and societal impacts. In the meantime, data privacy and ownership has become more and more critical in many domains, such as finance, health, government, and social networks. Federated learning (FL) has emerged to address data privacy issues. To make FL practically scalable, useful, efficient, and effective on security and privacy mechanisms and policies, it calls for joint efforts from the community, academia, and industry. More challenges, interplays, and tradeoffs in scalability, privacy, and security need to be investigated in a more holistic and comprehensive manner by the community. We are expecting broader, deeper, and greater evolution of these concepts and technologies, and confluence towards holistic trustworthy AI ecosystems.

This workshop provides an open forum for researchers, practitioners, and system builders to exchange ideas, discuss, and shape roadmaps towards scalable and privacy-preserving federated learning in particular, and scalable and trustworthy AI ecosystems in general.


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2020-12-12T08:20:00-08:00 - 2020-12-12T08:30:00-08:00
Opening Remarks
Xiaolin Andy Li
2020-12-12T08:30:00-08:00 - 2020-12-12T09:00:00-08:00
Keynote Talk 1: Dawn Song
2020-12-12T09:00:00-08:00 - 2020-12-12T09:15:00-08:00
A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning, Samuel Horváth and Peter Richtárik
2020-12-12T09:15:00-08:00 - 2020-12-12T09:30:00-08:00
Backdoor Attacks on Federated Meta-Learning, Chien-Lun Chen, Leana Golubchik and Marco Paolieri
2020-12-12T09:30:00-08:00 - 2020-12-12T09:45:00-08:00
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning, Hong-You Chen and Wei-Lun Chao
2020-12-12T09:45:00-08:00 - 2020-12-12T10:00:00-08:00
Preventing Backdoors in Federated Learningby Adjusting Server-side Learning Rate, Mustafa Ozdayi, Murat Kantarcioglu and Yulia Gel
2020-12-12T10:00:00-08:00 - 2020-12-12T10:30:00-08:00
Keynote Talk 2: H. Brendan McMahan
2020-12-12T10:30:00-08:00 - 2020-12-12T10:50:00-08:00
Lightning Talk Session 1: 10 papers, 2m each
2020-12-12T10:50:00-08:00 - 2020-12-12T11:20:00-08:00
Keynote Talk 3: Ruslan Salakhutdinov
2020-12-12T11:20:00-08:00 - 2020-12-12T11:35:00-08:00
FedML: A Research Library and Benchmark for Federated Machine Learning, Chaoyang He, et. al.
2020-12-12T11:35:00-08:00 - 2020-12-12T11:50:00-08:00
Learning to Attack Distributionally Robust Federated Learning, Wen Shen, Henger Li and Zizhan Zheng
2020-12-12T11:50:00-08:00 - 2020-12-12T12:20:00-08:00
Keynote Talk 4: Virginia Smith
2020-12-12T12:20:00-08:00 - 2020-12-12T12:36:00-08:00
Lightning Talk Session 2: 8 papers, 2m each
2020-12-12T12:36:00-08:00 - 2020-12-12T13:30:00-08:00
Poster Session 1
2020-12-12T13:30:00-08:00 - 2020-12-12T14:00:00-08:00
Keynote Talk 5: John C. Duchi
2020-12-12T14:00:00-08:00 - 2020-12-12T14:15:00-08:00
On Biased Compression for Distributed Learning, Aleksandr Beznosikov, Samuel Horváth, Mher Safaryan and Peter Richtarik
2020-12-12T14:15:00-08:00 - 2020-12-12T14:30:00-08:00
PAC Identifiability in Federated Personalization, Ben London
2020-12-12T14:30:00-08:00 - 2020-12-12T14:45:00-08:00
Model Pruning Enables Efficient Federated Learning on Edge Devices, Yuang Jiang, Shiqiang Wang, Victor Valls, Bong Jun Ko, Wei-Han Lee, Kin Leung and Leandros Tassiulas
2020-12-12T14:45:00-08:00 - 2020-12-12T15:00:00-08:00
Hybrid FL: Algorithms and Implementation, Xinwei Zhang, Tianyi Chen, Mingyi Hong and Wotao Yin
2020-12-12T15:00:00-08:00 - 2020-12-12T15:30:00-08:00
2020-12-12T15:30:00-08:00 - 2020-12-12T16:00:00-08:00
Keynote Talk 6: Tao Yang
2020-12-12T16:00:00-08:00 - 2020-12-12T16:20:00-08:00
Lightning Talk Session 3: 10 papers, 2m each
2020-12-12T16:20:00-08:00 - 2020-12-12T16:50:00-08:00
Keynote Talk 7: Tong Zhang
2020-12-12T16:50:00-08:00 - 2020-12-12T17:00:00-08:00
Lightning Talk Session 4: 5 papers, 2m each
2020-12-12T17:00:00-08:00 - 2020-12-12T18:00:00-08:00
Panel Discussion
2020-12-12T18:00:00-08:00 - 2020-12-12T19:00:00-08:00
Poster Session 2 (Papers presented in the afternoon)
2020-12-12T19:00:00-08:00 - 2020-12-12T19:10:00-08:00
Closing Remarks
Xiaolin Andy Li