A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
S.V.N. Vishwanathan and Nicol N. Schraudolph and Jin Yu and Simon Gunter

A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning.pdf 1.32MB
Type: Paper
Tags:

Metadata:
@article{11:39,author={Jin Yu and S.V.N. Vishwanathan and Simon Gunter and Nicol N. Schraudolph}, Title={A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning},journal={Journal of Machine Learning Research},volume={11}, url={http://www.jmlr.org/papers/volume11/yu10a/yu10a.pdf}}
Citation:
Vishwanathan, S., Schraudolph, N. N., Yu, J., & Gunter, S.. (2014). A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning [Data set]. Academic Torrents. https://academictorrents.com/details/81d30aec29d668644d9c0b4e64bc41bdefa2d929
No stats to report yet.

Send Feedback Start
   0.000007
DB Connect
   0.000625
Lookup hash in DB
   0.000443
Get torrent details
   0.000136
Get torrent details, finished
   0.000268
Get authors
   0.000002
Select authors
   0.000206
Parse bibtex
   0.000121
Write header
   0.000253
get stars
   0.000111
home tab
   0.000112
render right panel
   0.000005
render ads
   0.000502
fetch current hosters
   0.000247
Start get stats
   0.000346
End get stats
   0.000002
related datasets
   0.001566
Done