140 citations · 228 across the 16 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…
MCoCo: Multi-level Consistency Collaborative Multi-view Clustering
Yiyang Zhou, Qinghai Zheng, Wenbiao Yan +3
Multi-view clustering can explore consistent information from different views to guide clustering. Most existing works focus on pursuing shallow consistency in the feature space an…
Listen As You Wish: Audio based Event Detection via Text-to-Audio Grounding in Smart Cities
Haoyu Tang, Yunxiao Wang, Jihua Zhu +4
With the development of internet of things technologies, tremendous sensor audio data has been produced, which poses great challenges to audio-based event detection in smart cities…
Multi-view Hierarchical Clustering
Qinghai Zheng, Jihua Zhu, Shuangxun Ma
This paper focuses on the multi-view clustering, which aims to promote clustering results with multi-view data. Usually, most existing works suffer from the issues of parameter sel…
Multi-view Subspace Clustering Networks with Local and Global Graph Information
Qinghai Zheng, Jihua Zhu, Yuanyuan Ma +2
This study investigates the problem of multi-view subspace clustering, the goal of which is to explore the underlying grouping structure of data collected from different fields or…
Tensor-based Intrinsic Subspace Representation Learning for Multi-view Clustering
Qinghai Zheng, Yu Zhang, Jihua Zhu +3
As a hot research topic, many multi-view clustering approaches are proposed over the past few years. Nevertheless, most existing algorithms merely take the consensus information am…
Bidirectional Loss Function for Label Enhancement and Distribution Learning
Xinyuan Liu, Jihua Zhu, Qinghai Zheng +3
Label distribution learning (LDL) is an interpretable and general learning paradigm that has been applied in many real-world applications. In contrast to the simple logical vector…
Consistent and Complementary Graph Regularized Multi-view Subspace Clustering
Qinghai Zheng, Jihua Zhu, Zhongyu Li +3
This study investigates the problem of multi-view clustering, where multiple views contain consistent information and each view also includes complementary information. Exploration…
Generalized Label Enhancement with Sample Correlations
Qinghai Zheng, Jihua Zhu, Haoyu Tang +3
Recently, label distribution learning (LDL) has drawn much attention in machine learning, where LDL model is learned from labelel instances. Different from single-label and multi-l…
Constrained Bilinear Factorization Multi-view Subspace Clustering
Qinghai Zheng, Jihua Zhu, Zhiqiang Tian +3
Multi-view clustering is an important and fundamental problem. Many multi-view subspace clustering methods have been proposed, and most of them assume that all views share a same c…
Feature Concatenation Multi-view Subspace Clustering
Qinghai Zheng, Jihua Zhu, Zhongyu Li +3
Multi-view clustering is a learning paradigm based on multi-view data. Since statistic properties of different views are diverse, even incompatible, few approaches implement multi-…