end-to-end reinforcement learning
PulseAugur coverage of end-to-end reinforcement learning — every cluster mentioning end-to-end reinforcement learning across labs, papers, and developer communities, ranked by signal.
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Infant Movement Noise Enhances Deep Reinforcement Learning Exploration
Researchers have developed a novel exploration strategy for deep reinforcement learning inspired by the spontaneous movements of infants. This method introduces temporally correlated noise that mimics the developmental …
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New Survey Details Advances in End-to-End Multi-Speaker ASR
A new survey paper published on arXiv details advancements in end-to-end (E2E) multi-speaker automatic speech recognition (ASR) for monaural audio. The paper systematically reviews E2E neural approaches, categorizing th…
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GIFT: Global stabilisation via Intrinsic Fine Tuning
Researchers have introduced Global Stabilisation via Intrinsic Fine Tuning (GIFT), a new training framework designed to improve the stability of deep reinforcement learning (RL) policies. Current deep RL policies often …