Neural architecture search, imitation learning and the optimized pipeline with Dr. Debadeepta Dey

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Episode 108 | February 26, 2020

Dr. Debadeepta Dey is a Principal Researcher in the Adaptive Systems and Interaction group at MSR and he’s currently exploring several lines of research that may help bridge the gap between perception and planning for autonomous agents, teaching them to make decisions under uncertainty and even to stop and ask for directions when they get lost!

On today’s podcast, Dr. Dey talks about how his latest work in meta-reasoning helps improve modular system pipelines and how imitation learning hits the ML sweet spot between supervised and reinforcement learning. He also explains how neural architecture search helps enlighten the “dark arts” of neural network training and reveals how boredom, an old robot and several “book runs” between India and the US led to a rewarding career in research.

See more on this and other Microsoft Research podcast episodes: https://www.microsoft.com/en-us/research/blog/category/podcast/




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Tags:
Debadeepta Dey
Adaptive Systems and Interaction group
Microsoft Research
autonomous agents
meta-reasoning
modular system pipelines
imitation learning
reinforcement learning
neural network training
Microsoft Research Podcast