Hyderabad
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Provable Partially Observable Reinforcement Learning with Privileged Information Yang Cai
Partial observability of the underlying states generally presents significant challenges for reinforcement learning (RL).
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Limiting Extrapolation in Linear Approximate Value Iteration
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Neural Information Processing Systems http://nips.cc/
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DistributionallyRobustOptimizationwithData Geometry
It has been well documented that high dimensional data approximately resides on low dimensional manifolds.
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Concentration of risk measures: A Wasserstein distance approach
Sanjay P. Bhat, Prashanth L.A.
Using a different proof technique, the results are extended to the class of spectral risk measures having a bounded risk spectrum.
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