1 citations · 1 across the 4 of their papers we have counts for
5 papers
LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction
Jiakai Tang, Runfeng Zhang, Weiqiu Wang +7
Scaling Transformer-based click-through rate (CTR) models by stacking more parameters brings growing computational and storage overhead, creating a widening gap between scaling amb…
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection
Zining Chen, Xingshuang Luo, Weiqiu Wang +3
Recent Anomaly Detection (AD) methods have achieved great success with In-Distribution (ID) data. However, real-world data often exhibits distribution shift, causing huge performan…
PracticalDG: Perturbation Distillation on Vision-Language Models for Hybrid Domain Generalization
Zining Chen, Weiqiu Wang, Zhicheng Zhao +3
Domain Generalization (DG) aims to resolve distribution shifts between source and target domains, and current DG methods are default to the setting that data from source and target…
Causality-based Dual-Contrastive Learning Framework for Domain Generalization
Zining Chen, Weiqiu Wang, Zhicheng Zhao +1
Domain Generalization (DG) is essentially a sub-branch of out-of-distribution generalization, which trains models from multiple source domains and generalizes to unseen target doma…
Bag of Tricks for Out-of-Distribution Generalization
Zining Chen, Weiqiu Wang, Zhicheng Zhao +2
Recently, out-of-distribution (OOD) generalization has attracted attention to the robustness and generalization ability of deep learning based models, and accordingly, many strateg…