Name
Abstract | ||
|---|---|---|
Given any starting partition of a data space into N cells, we consider the problem of finding the optimal partition of the data space into blocks which are unions of cells. The algorithms we describe can be used to find the optimal partition of a set of data points in any dimension. These algorithms work for any strongly convex objective function that is additive on the blocks of a partition. We describe an ecient O(N2) dynamic programming algorithm for finding the optimal partition of N cells into arbitrary blocks (not necessarily connected) and we also give a branch and bound algorithm for finding the optimal partition of N cells into connected blocks. These results can be used to search for clusters in astronomical data, signal processing and in a variety of other applications. Subject headings: signal processing, galaxy clusters, data analysis, algo- rithms, dynamic programming, branch and bound |
Year | Venue | Keywords |
|---|---|---|
2010 | CIDU | galaxy clusters,branch and bound algorithm,branch and bound,data analysis,dynamic programming algorithm,objective function,subject headings,signal processing |
Field | DocType | Citations |
Data point,Discrete mathematics,Anomaly detection,Additive function,Convexity,Measurement uncertainty,Fitness function,Parameter space,Partition (number theory),Mathematics | Conference | 2 |
PageRank | References | Authors |
1.28 | 1 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bradley W. Jackson | 1 | 6 | 2.16 |
| Jeffrey D. Scargle | 2 | 80 | 10.24 |
| Chris Cusanza | 3 | 2 | 1.28 |
| David Barnes | 4 | 23 | 6.39 |
| Dennis Kanygin | 5 | 2 | 1.28 |
| Russell Sarmiento | 6 | 2 | 1.28 |
| Sowmya Subramaniam | 7 | 2 | 1.28 |
| Tzu-Wang Chuang | 8 | 2 | 1.28 |