5 citations · 13 across the 9 of their papers we have counts for
16 papers
Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory
Wenliang Zhong, Haoyu Tang, Qinghai Zheng +3
The rapid evolution of deep learning and large language models has led to an exponential growth in the demand for training data, prompting the development of Dataset Distillation m…
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models
Jinqian Chen, Jihua Zhu, Qinghai Zheng +2
Federated learning encounters substantial challenges with heterogeneous data, leading to performance degradation and convergence issues. While considerable progress has been achiev…
Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor
Jinqian Chen, Jihua Zhu, Qinghai Zheng
Federated learning encounters a critical challenge of data heterogeneity, adversely affecting the performance and convergence of the federated model. Various approaches have been p…
Label Information Bottleneck for Label Enhancement
Qinghai Zheng, Jihua Zhu, Haoyu Tang
In this work, we focus on the challenging problem of Label Enhancement (LE), which aims to exactly recover label distributions from logical labels, and present a novel Label Inform…
Semantically Consistent Multi-view Representation Learning
Yiyang Zhou, Qinghai Zheng, Shunshun Bai +1
In this work, we devote ourselves to the challenging task of Unsupervised Multi-view Representation Learning (UMRL), which requires learning a unified feature representation from m…
Multi-view Semantic Consistency based Information Bottleneck for Clustering
Wenbiao Yan, Jihua Zhu, Yiyang Zhou +2
Multi-view clustering can make use of multi-source information for unsupervised clustering. Most existing methods focus on learning a fused representation matrix, while ignoring th…