Training Large-Scale Deep Nets with RL with Nando de Freitas
EPISODE 213
|
DECEMBER
21,
2018
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About this Episode
Today we close out both our NeurIPS series and our 2018 conference coverage with this interview with Nando de Freitas, Team Lead & Principal Scientist at Deepmind and Fellow at the Canadian Institute for Advanced Research.
In our conversation, we explore his interest in understanding the brain and working towards artificial general intelligence through techniques like meta-learning, few-shot learning and imitation learning. In particular, we dig into a couple of his team's NeurIPS papers: "Playing hard exploration games by watching YouTube," and "One-Shot high-fidelity imitation: Training large-scale deep nets with RL."
About the Guest
Nando de Freitas
Google Deepmind
Resources
- DeepMind
- Canadian Institute for Advanced Research
- Paper: One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL
- Paper: Playing hard exploration games by watching YouTube
- Paper: Kunihiko Fukushima - Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position
- Paper: Yann LeCun - A Theoretical Framework for Backpropagation
- Misha Dneil
- Chelsea Finn - Check out our interview with Chelsea here!
- Paper: Neural Programmer-Interpreters
- Mujoco
- Deep Learning Indaba - Check out our Deep Learning Indaba series!
- TWIML Presents: NeurIPS Series page