IEEE

Dynamic Multi-Level Competition Learning-Based Dual-Task Optimization for High-Dimensional Feature Selection

Abstract: Feature selection (FS) is a critical task in data science and machine learning, presenting significant challenges in high-dimensional settings due to the complexity and noise inherent in ...
IEEE

Resource-Aware Neural Network Pruning Using Constrained Reinforcement Learning and Self-Competition

This paper presents a novel approach to neural network pruning by integrating a self-competition reward system into an Automated Machine Learning (AutoML) pruning framework. Traditional pruning ...