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Adaptive Federated Learning for Communication and Computation Efficiency (2021 IEEE Leonard Prize-winning work).
Shiqiang Wang

Federated learning is a recent and rapidly expanding area of machine learning that allows parties to benefit from joint training of models whilst respecting the privacy of each party's data. IBM Research has a broad effort in federated learning comprising novel methods, models and paradigms and offers an enterprise-strength federated learning platform free to use for non-commercial purposes, the IBM Federated Learning Community Edition.

The session will give an overview through a series of 7 short talks on the most exciting new research results from IBM Research in federated learning. Questions shall be collected using the Chat window and addressed after the lightning talks as well as after the live-interactive demo.

Author Information

Shiqiang Wang (IBM Research)

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