3 papers
cs.LG2025
Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
Xueqing Sun, Renzhen Wang, Quanziang Wang +3
Pseudo-labeling is a commonly used paradigm in semi-supervised learning, yet its application to semi-supervised regression (SSR) remains relatively under-explored. Unlike classific…
cs.LG2025
Data-Distill-Net: A Data Distillation Approach Tailored for Reply-based Continual Learning
Wenyang Liao, Quanziang Wang, Yichen Wu +2
Replay-based continual learning (CL) methods assume that models trained on a small subset can also effectively minimize the empirical risk of the complete dataset. These methods ma…
cs.CV2025
Singular Value Fine-tuning for Few-Shot Class-Incremental Learning
Zhiwu Wang, Yichen Wu, Renzhen Wang +4
Class-Incremental Learning (CIL) aims to prevent catastrophic forgetting of previously learned classes while sequentially incorporating new ones. The more challenging Few-shot CIL…