RSS Feed - Blog
About: A stochastic variant of the mirror descent algorithm employing Langford and Zhang's truncated gradient idea to minimize L1 regularized loss minimization problems for classification and regression. Changes:Fixed major bug in implementation. The components of the iterate where the current example vector is zero were not being updated correctly. Thanks to Jonathan Chang for pointing out the error to us.
|
Projects that are tagged with mirror descent.
Search
Manage
Sort by
Filter by
Latest Thoughts
- MLOSS workshop at ICML 2015: Open Ecosystems
by Antti Honkela on March 30, 2015
- A third of the top 100 papers are about software
by Cheng Soon Ong on October 30, 2014
- Open Machine Learning Workshop
by Cheng Soon Ong on July 28, 2014
- Machine Learning Distro
by Cheng Soon Ong on July 22, 2014
- Google Summer of Code 2014
by Cheng Soon Ong on June 3, 2014
- Reproducibility is not simple
by Cheng Soon Ong on March 30, 2014
- Keynotes at ACML 2013
by Cheng Soon Ong on November 14, 2013
- What does the “OSS” in MLOSS mean?
by Mark Reid on September 1, 2013
- Code review for science
by Cheng Soon Ong on August 14, 2013
- GSoC 2013
by Cheng Soon Ong on April 9, 2013
No forum yet.
