activity
20152019
most citedLogDet Rank Minimization with Application to Subspace Clustering

41 citations · 71 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG20196 cited

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…

eess.SP201921 cited

Automated Classification of Seizures against Nonseizures: A Deep Learning Approach

Xinghua Yao, Qiang Cheng, Guo-Qiang Zhang

In current clinical practice, electroencephalograms (EEG) are reviewed and analyzed by well-trained neurologists to provide supports for therapeutic decisions. The way of manual re…

cs.LG20173 cited

Unified Spectral Clustering with Optimal Graph

Zhao Kang, Chong Peng, Qiang Cheng +1

Spectral clustering has found extensive use in many areas. Most traditional spectral clustering algorithms work in three separate steps: similarity graph construction; continuous l…

cs.LG2017

Twin Learning for Similarity and Clustering: A Unified Kernel Approach

Zhao Kang, Chong Peng, Qiang Cheng

Many similarity-based clustering methods work in two separate steps including similarity matrix computation and subsequent spectral clustering. However, similarity measurement is c…

cs.IR2016

Top-N Recommendation with Novel Rank Approximation

Zhao Kang, Qiang Cheng

The importance of accurate recommender systems has been widely recognized by academia and industry. However, the recommendation quality is still rather low. Recently, a linear spar…

cs.CV201541 cited

LogDet Rank Minimization with Application to Subspace Clustering

Zhao Kang, Chong Peng, Jie Cheng +1

Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. Howeve…