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Virtual Event
July 30–August 1, 2020
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Thursday, July 30 • 20:10 - 20:40
Brings Federated Learning to Kubeflow With FATE-Operator - Layne Peng & Jiahao Chen, VMware

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Federated Machine Learning (FML) is a one of the most promising machine learning technologies to solve data silos and strengthening of data privacy and security, which allows collaborating organizations to create models without leaking data privacy. FATE is an open source project providing a secure MPC framework to support FML architecture. The challenge of FML is how to coordinate different parties usually reside in different geographical location.

This talk will introduce how we do FML in Kubernetes by Kubeflow. The flexibility and scalability of Kubernetes helps a lot on customizing our platform requirements to fit FML. A FATE-Operator is designed to run FML jobs on Kubernetes, which fit FML into existed Kubeflow ecosystem.

In this session, audience will learning:
1. What is FML?
2. How to design a Kubernetes Operator;
3. The experience of running FML in Kubernetes.
Speakers
avatar for Jiahao Chen

Jiahao Chen

Software Engineer, Tencent
Jiahao Chen, software engineer at Tencent, specializes in container, network and distributed technology research, and is also actively involved in the construction of open source communities. During his tenure at Tencent, he led or participated in the completion of the construction... Read More →
avatar for Layne Peng

Layne Peng

Staff Researcher, VMware
Layne Peng is a tech lead in VMware's CTO Office, where he leads cutting-edge federated learning initiatives. Layne is a respected Technical Steering Committee member of both FATE and OpenFL. He is the primary maintainer of FATE, an open-source federated learning framework, and the... Read More →

Brings Federated Learning to Kubeflow with FATE Operator pdf
Thursday July 30, 2020 20:10 - 20:40 CST
Virtual Room 3
  Customizing + Extending Kubernetes