Name
Abstract | ||
|---|---|---|
This paper addresses the problem of grouping the data points sampled from a union of multiple subspaces in the presence of outliers. Information theoretic objective functions are proposed to combine structured low-rank representations (LRRs) to capture the global structure of data and information theoretic measures to handle outliers. In theoretical part, we point out that group sparsity-induced m... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TNNLS.2015.2500600 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Robustness,Clustering methods,Sparse matrices,Dictionaries,Clustering algorithms,Minimization,Atmospheric measurements | Data point,Fuzzy clustering,CURE data clustering algorithm,Correlation clustering,Pattern recognition,Computer science,Linear subspace,Constrained clustering,Artificial intelligence,Cluster analysis,Machine learning,Kernel density estimation | Journal |
Volume | Issue | ISSN |
27 | 12 | 2162-237X |
Citations | PageRank | References |
8 | 0.43 | 47 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran He | 1 | 1790 | 108.39 |
| Liang Wang | 2 | 4317 | 243.28 |
| Zhenan Sun | 3 | 2379 | 139.49 |
| Yingya Zhang | 4 | 21 | 3.81 |
| Baochun Li | 5 | 9416 | 614.20 |