Zhao Kang(康昭)
Zhao Kang(康昭)
Computer Science, University of Electronic Science and Technology of China (电子科技大学)
Verified email at uestc.edu.cn - Homepage
TitleCited byYear
Robust PCA via Nonconvex Rank Approximation
Z Kang, C Peng, Q Cheng
The IEEE International Conference on Data Mining (ICDM 2015), 2015
High-resolution gamma-ray spectroscopy with a microwave-multiplexed transition-edge sensor array
O Noroozian, JAB Mates, DA Bennett, JA Brevik, JW Fowler, J Gao, ...
Applied Physics Letters 103 (20), 202602, 2013
Top-N Recommender System via Matrix Completion
Z Kang, C Peng, Q Cheng
Thirtieth AAAI Conference on Artificial Intelligence(AAAI-16), 2016
Kernel-driven Similarity Learning
Z Kang, C Peng, Q Cheng
Neurocomputing 267, 210-219, 2017
Subspace clustering using log-determinant rank approximation
C Peng, Z Kang, huiqing li, qiang Cheng
ACM KDD 2015, 2015
Robust Subspace Clustering via Smoothed Rank Approximation
Z Kang, P Chong, C Qiang
IEEE Signal Processing Letters 22 (11), 2088-2092, 2015
Twin Learning for Similarity and Clustering: A Unified Kernel Approach
Z Kang, C Peng, Q Cheng
Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017
Feature Selection Embedded Subspace Clustering
C Peng, Z Kang, M Yang, Q Cheng
IEEE Signal Processing Letters, 2016
Low-rank Kernel Learning for Graph-based Clustering
Z Kang, L Wen, W Chen, Z Xu
Knowledge-Based Systems 163, 510-517, 2019
Unified Spectral Clustering with Optimal Graph
Z Kang, C Peng, Q Cheng, Z Xu
The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2018
Self-weighted multi-view clustering with soft capped norm
S Huang, Z Kang, Z Xu
Knowledge-Based Systems 158, 1-8, 2018
Subspace Clustering via Variance Regularized Ridge Regression
C Peng, Z Kang, Q Cheng
Conference on Computer Vision and Pattern Recognition (CVPR 2017), 2017
Robust subspace clustering via tighter rank approximation
zhao kang, P Chong, C Qiang
ACM CIKM'15, 2015
LogDet Rank Minimization with Application to Subspace Clustering
kang zhao, P Chong, C Jie, C Qiang
Computational Intelligence and Neuroscience 2015, 2015
Integrating Feature and Graph Learning with Low-Rank Representation
C Peng, Z Kang, Q Cheng
Neurocomputing, 2017
Auto-weighted multi-view clustering via kernelized graph learning
S Huang, Z Kang, IW Tsang, Z Xu
Pattern Recognition 88, 174-184, 2019
Robust Graph Regularized Nonnegative Matrix Factorization for Clustering
C Peng, Z Kang, Y Hu, Q Cheng
ACM Transactions on Knowledge Discovery from Data 11 (3), 2017
Top-n recommendation on graphs
Z Kang, C Peng, M Yang, Q Cheng
Proceedings of the 25th ACM International on Conference on Information and …, 2016
Neutralino reconstruction at the LHC fromádecay-frameákinematics
Z Kang, N Kersting, S Kraml, AR Raklev, MJ White
The European Physical Journal C 70 (1-2), 271-283, 2010
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification
Z Kang, X Lu, J Yi, Z Xu
The 27th International Joint Conference on Artificial Intelligence (IJCAI-18), 2018
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