Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
Work
Year: 2015
Type: article
Abstract: We show how to approximate a data matrix A with a much smaller sketch ~A that can be used to solve a general class of constrained k-rank approximation problems to within (1+ε) error. Importantly, this... more
Institution Massachusetts Institute of Technology
Cites: 46
Cited by: 293
Related to: 10
FWCI: 26.41
Citation percentile (by year/subfield): 93.61
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funders National Science Foundation, Defense Advanced Research Projects Agency, Air Force Office of Scientific Research
Grant IDS 1111109,CCF-AF-0937274,CCF-0939370,CCF-1217506,IIS-0835652, FA8650-11-C-7192, FA9550-13-1-0042