most citedRepresentation Learning for Continuous Action Spaces is Beneficial for Efficient Policy Learning

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.LG2022★ 1 cited

Representation Learning for Continuous Action Spaces is Beneficial for Efficient Policy Learning

Tingting Zhao, Ying Wang, Wei Sun +3

Deep reinforcement learning (DRL) breaks through the bottlenecks of traditional reinforcement learning (RL) with the help of the perception capability of deep learning and has been…

cs.AI2022

Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification

Yuan Wang, Huiling Song, Peng Huo +4

Extreme multi-label text classification (XMTC) refers to the problem of tagging a given text with the most relevant subset of labels from a large label set. A majority of labels on…