A sparse version of the ridge logistic regression for large-scale text categorization-Reference-Cited by-同舟云学术

A sparse version of the ridge logistic regression for large-scale text categorization

Published:2011-01 Issue:2 Volume:32 Page:101-106
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Aseervatham Sujeevan,Antoniadis Anestis,Gaussier Eric,Burlet Michel,Denneulin Yves

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference23 articles.

1. Regularization of wavelet approximations;Antoniadis;J. Amer. Statist. Assoc.,2001

2. Bolasso: Model consistent LASSO estimation through the bootstrap;Bach,2008

3. Map-reduce for machine learning on multicore;Chu,2006

4. Least angle regression;Efron;Ann. Statist.,2004

5. Friedman, J., Hastie, T., Tibshirani, R., 2008. Regularization paths for generalized linear models via coordinate descent. Tech. Rep., Dept. of Statistics, Stanford University.

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