Day 1 Lightning Talks: Federated Optimization and Analytics

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