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

Send Feedback Start
   0.000009
DB Connect
   0.000711
Lookup hash in DB
   0.000583
Get torrent details
   0.000181
Get torrent details, finished
   0.000347
Get authors
   0.000001
Select authors
   0.000281
Parse bibtex
   0.000133
Write header
   0.000650
get stars
   0.000163
home tab
   0.000183
render right panel
   0.000006
render ads
   0.000666
fetch current hosters
   0.000339
related datasets
   0.002417
Done