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IBM Federated Learning Community Edition: An Interactive Demonstration
Laura Wynter · Chaitanya Kumar · Pengqian Yu · Mikhail Yurochkin · Amogh Tarcar

Tue Dec 08 07:00 AM -- 07:20 AM & Wed Dec 09 07:00 AM -- 07:20 AM (PST) @

Federated Learning (FL) is a means to train machine learning models without centralizing data. To deal with the ever-growing demands for training data whilst respecting data privacy and confidentiality, it has become important to move from centralized to federated machine learning. The IBM Federated Learning Community Edition is one means for achieving this goal; it is a platform and library, free to use for non-commercial purposes, with built-in features that facilitate enterprise-strength applications: \url{https://github.com/IBM/federated-learning-lib}. This interactive demo session highlights several featured algorithms available only in the IBM Federated Learning Community Edition, and provides tutorials, audience-interactive examples, and a guest speaker from the tech company Persistent Systems who has used the IBM Federated Learning Community Edition for Covid-19 outcome prediction for hospitals.

Author Information

Laura Wynter (IBM Research)
Chaitanya Kumar (IBM Research)
Pengqian Yu (IBM)

Dr. Pengqian Yu is a Research Scientist in AI with IBM, where he works on deep reinforcement and federated learning algorithms and their applications to real-world problems. His research interests include sequential decision-making, optimization, and learning in large-scale complex and uncertain systems: robust/convex/non-convex optimization, ambiguity-averse and risk-aware Markov decision processes, approximate dynamic programming and deep reinforcement learning. Prior to joining IBM, Dr. Yu was a Research Scientist at Neuri Pte Ltd, and a Digital Solution Consultant at DNV GL. He received his Ph.D. degree from the National University of Singapore (NUS) advised by Dr. Huan Xu and was a Research Fellow at NUS with Dr. William Benjamin Haskell. He was a research intern at IBM Research Ireland mentored by Dr. Jia Yuan Yu.

Mikhail Yurochkin (IBM Research, MIT-IBM Watson AI Lab)
Amogh Tarcar (Persistent Systems)

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