Abstract: Label distribution learning (LDL) is a novel machine learning paradigm that can be seen as an extension of multi-label learning (MLL). Compared with MLL, the advantages of LDL are reflected ...
Abstract: Offline Reinforcement Learning (RL) methods leverage previous experiences to learn better policies than the behavior policy used for data collection. However, they face challenges handling ...
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