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cs.LG2021
Memory-based Deep Reinforcement Learning for POMDPs
Lingheng Meng, Rob Gorbet, Dana Kulić
A promising characteristic of Deep Reinforcement Learning (DRL) is its capability to learn optimal policy in an end-to-end manner without relying on feature engineering. However, m…
cs.LG2020
Fast Approximate Multi-output Gaussian Processes
Vladimir Joukov, Dana Kulić
Gaussian processes regression models are an appealing machine learning method as they learn expressive non-linear models from exemplar data with minimal parameter tuning and estima…