49 citations · 169 across the 17 of their papers we have counts for
10 papers · 1 filter
Log-based Sparse Nonnegative Matrix Factorization for Data Representation
Chong Peng, Yiqun Zhang, Yongyong Chen +3
Nonnegative matrix factorization (NMF) has been widely studied in recent years due to its effectiveness in representing nonnegative data with parts-based representations. For NMF,…
Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view
Zhao Kang, Zhiping Lin, Xiaofeng Zhu +1
Graph-based subspace clustering methods have exhibited promising performance. However, they still suffer some of these drawbacks: encounter the expensive time overhead, fail in exp…
Structured Graph Learning for Clustering and Semi-supervised Classification
Zhao Kang, Chong Peng, Qiang Cheng +4
Graphs have become increasingly popular in modeling structures and interactions in a wide variety of problems during the last decade. Graph-based clustering and semi-supervised cla…
Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering
Chong Peng, Zhilu Zhang, Zhao Kang +2
In this paper, we propose a new Semi-Nonnegative Matrix Factorization method for 2-dimensional (2D) data, named TS-NMF. It overcomes the drawback of existing methods that seriously…
Multi-view Subspace Clustering via Partition Fusion
Juncheng Lv, Zhao Kang, Boyu Wang +2
Multi-view clustering is an important approach to analyze multi-view data in an unsupervised way. Among various methods, the multi-view subspace clustering approach has gained incr…
Structure Learning with Similarity Preserving
Zhao Kang, Xiao Lu, Yiwei Lu +2
Leveraging on the underlying low-dimensional structure of data, low-rank and sparse modeling approaches have achieved great success in a wide range of applications. However, in man…
Multi-graph Fusion for Multi-view Spectral Clustering
Zhao Kang, Guoxin Shi, Shudong Huang +4
A panoply of multi-view clustering algorithms has been developed to deal with prevalent multi-view data. Among them, spectral clustering-based methods have drawn much attention and…
Latent Multi-view Semi-Supervised Classification
Xiaofan Bo, Zhao Kang, Zhitong Zhao +2
To explore underlying complementary information from multiple views, in this paper, we propose a novel Latent Multi-view Semi-Supervised Classification (LMSSC) method. Unlike most…
Nonnegative Matrix Factorization with Local Similarity Learning
Chong Peng, Zhao Kang, Chenglizhao Chen +1
Existing nonnegative matrix factorization methods focus on learning global structure of the data to construct basis and coefficient matrices, which ignores the local structure that…
RES-PCA: A Scalable Approach to Recovering Low-rank Matrices
Chong Peng, Chenglizhao Chen, Zhao Kang +2
Robust principal component analysis (RPCA) has drawn significant attentions due to its powerful capability in recovering low-rank matrices as well as successful appplications in va…