11 citations · 17 across the 4 of their papers we have counts for
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cs.LG2020★ 2 cited
Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop
Wei Fan, Kunpeng Liu, Hao Liu +3
We study the problem of balancing effectiveness and efficiency in automated feature selection. After exploring many feature selection methods, we observe a computational dilemma: 1…
cs.LG2020★ 4 cited
AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement Learning
Wei Fan, Kunpeng Liu, Hao Liu +3
In this paper, we study the problem of balancing effectiveness and efficiency in automated feature selection. Feature selection is a fundamental intelligence for machine learning a…
cs.LG2014★ 11 cited
Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval
Liang Wu, Hui Xiong, Liang Du +6
The problem of software artifact retrieval has the goal to effectively locate software artifacts, such as a piece of source code, in a large code repository. This problem has been…