2 papers
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…
cs.LG2013
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration
Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt +2
The policy gradient approach is a flexible and powerful reinforcement learning method particularly for problems with continuous actions such as robot control. A common challenge in…