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The Ethereal
Communication-efficient sparse regression: a one-shot approach
March 14, 2015 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Jason D. Lee, Yuekai Sun, Qiang Liu, Jonathan E. Taylor
arXiv ID
1503.04337
Category
stat.ML: Machine Learning (Stat)
Cross-listed
cs.LG
Citations
68
Venue
arXiv.org
Last Checked
6 months ago
Abstract
We devise a one-shot approach to distributed sparse regression in the high-dimensional setting. The key idea is to average "debiased" or "desparsified" lasso estimators. We show the approach converges at the same rate as the lasso as long as the dataset is not split across too many machines. We also extend the approach to generalized linear models.
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