2 papers
cs.LG2025
Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
Yongqi Ding, Lin Zuo, Mengmeng Jing +3
Brain-inspired spiking neural networks (SNNs) promise to be a low-power alternative to computationally intensive artificial neural networks (ANNs), although performance gaps persis…
cs.CV2025
SWAT: Sliding Window Adversarial Training for Gradual Domain Adaptation
Zixi Wang, Xiangxu Zhao, Tonglan Xie +2
Domain shifts are critical issues that harm the performance of machine learning. Unsupervised Domain Adaptation (UDA) mitigates this issue but suffers when the domain shifts are st…