Project details for OptWok

Screenshot OptWok 0.2

by ong - May 1, 2011, 15:30:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems.


  • python 2.5+
  • cvxopt 1.0+ (for solving linear and quadratic programs)
  • pythongrid (for using a cluster)
  • cython 0.14.1 (for speeding up kernel computations)

This package includes software from the following projects: - slycot (for solving Sylvester equation, see README.slycot).


The projects currently prototyped: - learning the output kernel using block coordinate descent - difference of convex functions algorithms for sparse classfication

Learning the output kernel using block coordinate descent

  • The workhorse is, which implements a framework for minimizing the invex function for learning the kernel on outputs.
  • gives usage examples.
Changes to previous version:

Initial Announcement on

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: Matlab, Numpy
Tags: Kernel Learning
Archive: download here


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