An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
Kwangmoo Koh and Seung-Jean Kim and Stephen Boyd

An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression.pdf 910.98kB
Type: Paper
Tags:

Metadata:
@article{8:54,author={Kwangmoo Koh and Seung-Jean Kim and Stephen Boyd}, Title={An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression},journal={Journal of Machine Learning Research},volume={8}, url={http://www.jmlr.org/papers/volume8/koh07a/koh07a.pdf}}
Citation:
Koh, K., Kim, S., & Boyd, S.. (2014). An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression [Data set]. Academic Torrents. https://academictorrents.com/details/2deb1384378d8b6b777db438b4f57ff7866274a5

Send Feedback Start
   0.000024
DB Connect
   0.000458
Lookup hash in DB
   0.000444
Get torrent details
   0.000149
Get torrent details, finished
   0.000277
Get authors
   0.000001
Select authors
   0.000197
Parse bibtex
   0.000100
Write header
   0.000231
get stars
   0.000146
home tab
   0.000129
render right panel
   0.000006
render ads
   0.000396
fetch current hosters
   0.000239
related datasets
   0.001527
Done