2 papers
cs.LG2025
A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
Johnny R. Zhang, Xiaomei Mi, Gaoyuan Du +4
Stochastic optimization powers the scalability of modern artificial intelligence, spanning machine learning, deep learning, reinforcement learning, and large language model trainin…
cs.LG2025
Multi-label feature selection based on binary hashing learning and dynamic graph constraints
Cong Guo, Changqin Huang, Wenhua Zhou +1
Multi-label learning poses significant challenges in extracting reliable supervisory signals from the label space. Existing approaches often employ continuous pseudo-labels to repl…