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cs.LG2022
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking
Julius Ott, Lorenzo Servadei, Gianfranco Mauro +3
Nowadays, Deep Learning (DL) methods often overcome the limitations of traditional signal processing approaches. Nevertheless, DL methods are barely applied in real-life applicatio…
cs.LG2022
MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling
Julius Ott, Lorenzo Servadei, Jose Arjona-Medina +7
Data selection is essential for any data-based optimization technique, such as Reinforcement Learning. State-of-the-art sampling strategies for the experience replay buffer improve…