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cs.LG2026
Towards Robust Universal Perturbation Attacks: A Float-Coded, Penalty-Driven Evolutionary Approach
Shiqi Wang, Mahdi Khosravy, Neeraj Gupta +1
Universal adversarial perturbations (UAPs) have garnered significant attention due to their ability to undermine deep neural networks across multiple inputs using a single noise pa…
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…