Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli - TWiML Talk #177

Show notes

Today we’re joined by Kamyar Azizzadenesheli, PhD student at the University of California, Irvine, who joins us to review the core elements of RL, along with a pair of his RL-related papers: “Efficient Exploration through Bayesian Deep Q-Networks” and “Sample-Efficient Deep RL with Generative Adversarial Tree Search.” To skip the Deep Reinforcement Learning primer conversation and jump to the research discussion, skip to the 34:30 mark of the episode. Show notes at https://twimlai.com/talk/177

Guests

Kamyar Azizzadenesheli

Staff Researcher

NVIDIAPurdue UniversityUniversity of California, Irvine