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The Ethereal
NP-Hardness and Inapproximability of Sparse PCA
February 19, 2015 ยท Declared Dead ยท ๐ Information Processing Letters
"No code URL or promise found in abstract"
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Authors
Malik Magdon-Ismail
arXiv ID
1502.05675
Category
cs.LG: Machine Learning
Cross-listed
cs.CC,
cs.DS,
math.CO,
stat.ML
Citations
44
Venue
Information Processing Letters
Last Checked
6 months ago
Abstract
We give a reduction from {\sc clique} to establish that sparse PCA is NP-hard. The reduction has a gap which we use to exclude an FPTAS for sparse PCA (unless P=NP). Under weaker complexity assumptions, we also exclude polynomial constant-factor approximation algorithms.
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