Day 1 Lightning Talks: Federated Optimization and Analytics

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United States Google TechTalks
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Published on ● Video Link: https://www.youtube.com/watch?v=aD3o_f7tf28


Duration: 1:02:11
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A Google TechTalk, presented by 8 Speakers, 2021/11/8
ABSTRACT: Lightning Talks are 7 minutes plus questions.

Track 2 - Session Chair: Shanshan Wu (Federated Optimization & Analytics)

1. Peter Richtarik - EF21: A new, simpler, theoretically better, and practically faster error feedback
2. Zach Charles - On Large-Cohort Training for Federated Learning
3. Gauri Joshi - Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
4. Nicolas Lane - Scaling and Accelerating Federated Learning Research with Flower
5. Andrew Hard - Mixing Federated and Centralized Training
6.Ayfer Ozgur - From worst-case to pointwise bounds for distributed estimation under communication constraints
7. Walid Saad - Distributed Learning and Wireless Networks: A Closer Union
8. Phillip Gibbons - Federated Learning under Distributed Concept Drift

For abstracts of the talks and speaker bios, please see https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/speakers/#content

For more information about the workshop: https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/#content



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