TalkRL: Reinforcement Learning Interviews

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Summary

Kamyar Azizzadenesheli brings us insight on Bayesian RL, Generative Adversarial Tree search, what goes into great RL papers, and much more!

Show Notes

Dr. Kamyar Azizzadenesheli is a post-doctorate scholar at Caltech.  His research interest is mainly in the area of Machine Learning, from theory to practice, with the main focus in Reinforcement Learning.  He will be joining Purdue University as an Assistant CS Professor in Fall 2020.

Featured References

Efficient Exploration through Bayesian Deep Q-Networks
Kamyar Azizzadenesheli, Animashree Anandkumar

Surprising Negative Results for Generative Adversarial Tree Search
Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Zachary C Lipton, Animashree Anandkumar

Maybe a few considerations in Reinforcement Learning Research?
Kamyar Azizzadenesheli


Additional References






What is TalkRL: Reinforcement Learning Interviews?

TalkRL podcast is All Reinforcement Learning, All the time. In-depth interviews with brilliant people at the forefront of RL research and practice. Guests from places like MILA, MIT, DeepMind, Google Brain, Brown, Caltech, and more. Hosted by Robin Ranjit Singh Chauhan. Technical content.