8 citations · 8 across the 10 of their papers we have counts for
6 papers · 1 filter
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Xuanqian Wang, Jing Li, Ivor W. Tsang +1
Due to privacy and security concerns, recent advancements in group fairness advocate for model training regardless of demographic information. However, most methods still require p…
Alpha and Prejudice: Improving -sized Worst-case Fairness via Intrinsic Reweighting
Jing Li, Yinghua Yao, Yuangang Pan +3
Worst-case fairness with off-the-shelf demographics achieves group parity by maximizing the model utility of the worst-off group. Nevertheless, demographic information is often una…
Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao
Xu Chen, Zida Cheng, Yuangang Pan +6
Existing click-through rate (CTR) prediction works have studied the role of feature interaction through a variety of techniques. Each interaction technique exhibits its own strengt…
Self-Assessed Generation: Trustworthy Label Generation for Optical Flow and Stereo Matching in Real-world
Han Ling, Yinghui Sun, Quansen Sun +2
A significant challenge facing current optical flow and stereo methods is the difficulty in generalizing them well to the real world. This is mainly due to the high costs required…
PROUD: PaRetO-gUided Diffusion Model for Multi-objective Generation
Yinghua Yao, Yuangang Pan, Jing Li +2
Recent advancements in the realm of deep generative models focus on generating samples that satisfy multiple desired properties. However, prevalent approaches optimize these proper…
HCL: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding
Bowen Xing, Ivor W. Tsang
State-of-the-art model for zero-shot cross-lingual spoken language understanding performs cross-lingual unsupervised contrastive learning to achieve the label-agnostic semantic ali…