Optimization
Robust Bayesian Satisficing
Neural Information Processing Systems
Distributional shifts pose a significant challenge to achieving robustness in contemporary machine learning.
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Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
Neural Information Processing Systems
We further discuss the sample complexity for a desired approximation accuracy.
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