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The Ethereal
On the complexity of switching linear regression
October 23, 2015 ยท Declared Dead ยท ๐ at - Automatisierungstechnik
"No code URL or promise found in abstract"
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Authors
Fabien Lauer
arXiv ID
1510.06920
Category
stat.ML: Machine Learning (Stat)
Cross-listed
cs.CC,
cs.LG
Citations
33
Venue
at - Automatisierungstechnik
Last Checked
6 months ago
Abstract
This technical note extends recent results on the computational complexity of globally minimizing the error of piecewise-affine models to the related problem of minimizing the error of switching linear regression models. In particular, we show that, on the one hand the problem is NP-hard, but on the other hand, it admits a polynomial-time algorithm with respect to the number of data points for any fixed data dimension and number of modes.
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