4.3k citations · 5.5k across the 13 of their papers we have counts for
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cs.LG2018★ 26 cited
Supervising strong learners by amplifying weak experts
Paul Christiano, Buck Shlegeris, Dario Amodei
Many real world learning tasks involve complex or hard-to-specify objectives, and using an easier-to-specify proxy can lead to poor performance or misaligned behavior. One solution…
cs.LG2016★ 213 cited
A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
Chelsea Finn, Paul Christiano, Pieter Abbeel +1
Generative adversarial networks (GANs) are a recently proposed class of generative models in which a generator is trained to optimize a cost function that is being simultaneously l…