29 citations · 65 across the 13 of their papers we have counts for
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cs.LG2019★ 2 cited
PAC Reinforcement Learning without Real-World Feedback
Yuren Zhong, Aniket Anand Deshmukh, Clayton Scott
This work studies reinforcement learning in the Sim-to-Real setting, in which an agent is first trained on a number of simulators before being deployed in the real world, with the…
cs.LG2016
Mixture Proportion Estimation via Kernel Embedding of Distributions
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
Mixture proportion estimation (MPE) is the problem of estimating the weight of a component distribution in a mixture, given samples from the mixture and component. This problem con…