14–17 Oct 2019

Edward Oakes
PhD Student, UC Berkeley Electrical Engineering & Computer Sciences

Edward Oakes is a second-year PhD student at UC Berkeley and a contributor to the Ray project. Previously, he worked on isolation mechanisms for serverless computing and infrastructure for microservice deployments.

Sessions

9:00–12:30 Tuesday, 15 October 2019

Location: Blenheim Room - Palace Suite

Scalable AI and reinforcement learning with Ray

Secondary topics: Machine Learning, Machine Learning tools, Reinforcement Learning

Edward Oakes (UC Berkeley Electrical Engineering & Computer Sciences), Peter Schafhalter (UC Berkeley RISELab), Kristian Hartikainen (University of Oxford)

Average rating:

(5.00, 5 ratings)

Edward Oakes, Peter Schafhalter, and Kristian Hartikainen take a deep dive into Ray, a new distributed execution framework for distributed AI applications developed by machine learning and systems researchers at RISELab, and explore Ray’s API and system architecture and sharing application examples, including several state-of-the-art distributed training, hyperparameter search, and RL algorithms. Read more.