activity
20222024
most citedSemantic Invariant Multi-view Clustering with Fully Incomplete Information

63 citations · 96 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2024

Multimodal Fusion on Low-quality Data: A Comprehensive Survey

Qingyang Zhang, Yake Wei, Zongbo Han +8

Multimodal fusion focuses on integrating information from multiple modalities with the goal of more accurate prediction, which has achieved remarkable progress in a wide range of s…

cs.LG2023★ 20 cited

Provable Dynamic Fusion for Low-Quality Multimodal Data

Qingyang Zhang, Haitao Wu, Changqing Zhang +4

The inherent challenge of multimodal fusion is to precisely capture the cross-modal correlation and flexibly conduct cross-modal interaction. To fully release the value of each mod…

cs.CV2023★ 1 cited

dugMatting: Decomposed-Uncertainty-Guided Matting

Jiawei Wu, Changqing Zhang, Zuoyong Li +3

Cutting out an object and estimating its opacity mask, known as image matting, is a key task in image and video editing. Due to the highly ill-posed issue, additional inputs, typic…

cs.CV2023★ 63 cited

Semantic Invariant Multi-view Clustering with Fully Incomplete Information

Pengxin Zeng, Mouxing Yang, Yiding Lu +3

Robust multi-view learning with incomplete information has received significant attention due to issues such as incomplete correspondences and incomplete instances that commonly af…

cs.LG2023★ 2 cited

Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification

Mengyao Xie, Zongbo Han, Changqing Zhang +2

Classifying incomplete multi-view data is inevitable since arbitrary view missing widely exists in real-world applications. Although great progress has been achieved, existing inco…

cs.LG2023

Reweighted Mixup for Subpopulation Shift

Zongbo Han, Zhipeng Liang, Fan Yang +8

Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different…

cs.LG2022★ 10 cited

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

Zongbo Han, Zhipeng Liang, Fan Yang +7

Subpopulation shift widely exists in many real-world machine learning applications, referring to the training and test distributions containing the same subpopulation groups but va…