3 papers
cs.LG2025
Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains
Zhuo He, Shuang Li, Wenze Song +4
Endowing deep models with the ability to generalize in dynamic scenarios is of vital significance for real-world deployment, given the continuous and complex changes in data distri…
cs.CV2025
Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation
Mingjia Li, Shuang Li, Tongrui Su +3
Capitalizing on the complementary advantages of generative and discriminative models has always been a compelling vision in machine learning, backed by a growing body of research.…
cs.LG2024
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
Zhongxiang Fan, Zhaocheng Liu, Jian Liang +5
This paper investigates the one-epoch overfitting phenomenon in Click-Through Rate (CTR) models, where performance notably declines at the start of the second epoch. Despite extens…