Exploring Provably Robust Blackbox Optimization For Reinforcement Learning
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- Making use of modern
- In this video we discuss
- Nika Haghtalab (UC Berkeley) https://simons.berkeley.edu/talks/tbd-478 Quantifying Uncertainty: Stochastic, Adversarial, and ...
- M19V01 Black box optimization
- Making use of modern
In-Depth Information on Provably Robust Blackbox Optimization For Reinforcement Learning
Interest in derivative-free Okay so few definitions A quick overview of our NIPS 2016 paper https://arxiv.org/abs/1603.05642. Paper submitted published in IEEE ICRA 2018 - https://arxiv.org/abs/1709.06917 The most data-efficient algorithms for ...
Paper (accepted at IROS 2017): https://arxiv.org/abs/1703.07261 The most data-efficient algorithms for
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