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Panel Discussion
Yoshua Bengio · Andrew Ng · Raia Hadsell · John Platt · Claire Monteleoni · Jennifer Chayes

Fri Jun 14 05:15 PM -- 06:00 PM (PDT) @ None

Author Information

Yoshua Bengio (Montreal Institute for Learning Algorithms)
Andrew Ng (Landing AI)
Raia Hadsell (DeepMind)

Raia Hadsell, a senior research scientist at DeepMind, has worked on deep learning and robotics problems for over 10 years. Her early research developed the notion of manifold learning using Siamese networks, which has been used extensively for invariant feature learning. After completing a PhD with Yann LeCun, which featured a self-supervised deep learning vision system for a mobile robot, her research continued at Carnegie Mellon’s Robotics Institute and SRI International, and in early 2014 she joined DeepMind in London to study artificial general intelligence. Her current research focuses on the challenge of continual learning for AI agents and robotic systems. While deep RL algorithms are capable of attaining superhuman performance on single tasks, they cannot transfer that performance to additional tasks, especially if experienced sequentially. She has proposed neural approaches such as policy distillation, progressive nets, and elastic weight consolidation to solve the problem of catastrophic forgetting and improve transfer learning.

John Platt (Google)
Claire Monteleoni (University of Colorado Boulder)
Jennifer Chayes (Microsoft Research)

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