most citedInteractive Reinforcement Learning for Feature Selection with Decision Tree in the Loop

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.SD2023★ 1 cited

Boosting Fast and High-Quality Speech Synthesis with Linear Diffusion

Haogeng Liu, Tao Wang, Jie Cao +2

Denoising Diffusion Probabilistic Models have shown extraordinary ability on various generative tasks. However, their slow inference speed renders them impractical in speech synthe…

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…