Name
Abstract | ||
|---|---|---|
For computing the k-means clustering of the streaming and distributed big sparse data, we present an algorithm to obtain the sparse coreset for the k-means in polynomial time. This algorithm is mainly based on the explicit form of the center of mass and the approximate k-means. Because of the existence of the approximation, the coreset of the output inevitably has a factor, which can be controlled to be a very small constant. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1142/S0217595919500064 | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH |
Keywords | Field | DocType |
k-Means clustering,coreset,streaming,approximation algorithm | Approximation algorithm,k-means clustering,Mathematical optimization,Streaming algorithm,Algorithm,Cluster analysis,Time complexity,Mathematics,Sparse matrix,Coreset | Journal |
Volume | Issue | ISSN |
36 | 1 | 0217-5959 |
Citations | PageRank | References |
1 | 0.36 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Li | 1 | 5 | 6.54 |
| Dachuan Xu | 2 | 92 | 27.82 |
| Dongmei Zhang | 3 | 1439 | 132.94 |
| Tong Zhang | 4 | 53 | 18.56 |