4 citations · 7 across the 4 of their papers we have counts for
4 papers
Deep Reinforcement Learning-Assisted Age-optimal Transmission Policy for HARQ-aided NOMA Networks
Kunpeng Liu, Aimin Li, Shaohua Wu
The recent interweaving of AI-6G technologies has sparked extensive research interest in further enhancing reliable and timely communications. \emph{Age of Information} (AoI), as a…
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…
Simplifying Reinforced Feature Selection via Restructured Choice Strategy of Single Agent
Xiaosa Zhao, Kunpeng Liu, Wei Fan +4
Feature selection aims to select a subset of features to optimize the performances of downstream predictive tasks. Recently, multi-agent reinforced feature selection (MARFS) has be…
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…