Changes between Version 13 and Version 14 of WikiStart
 Timestamp:
 Feb 12, 2009 2:46:55 PM (11 years ago)
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WikiStart
v13 v14 5 5 OPTIML stands for Optimization methods in Machine Learning. Right now this page contains three subprojects: 6 6 7 SVMQP ('''S'''upport '''V'''ector '''M'''achines '''Q'''uadratic '''P'''rogramming solver) is a software package that solves 2norm soft margin support vector machine [http://www.kernelmachines.org/ classification problem]. The problem is formulated as a convex QP of the following form7 1. VMQP ('''S'''upport '''V'''ector '''M'''achines '''Q'''uadratic '''P'''rogramming solver) is a software package that solves 2norm soft margin support vector machine [http://www.kernelmachines.org/ classification problem]. The problem is formulated as a convex QP of the following form 8 8 {{{ 9 9 min x'Qx  e'x … … 15 15 where {{{ e }}} is the vector of ones, {{{a}}} is a vector of lables (1 or 1) of the data, and {{{C}}} is the panalty parameter associated with the violation of the margin constraint. 16 16 17 1.SVMQP is designed for largescale SVM problems. The underlying algorithm is an active set method for convext QPs. [http://www.research.ibm.com/people/k/katya/incas.pdf/ Here ] is the paper describing the algorithm and containing computational comparison with [http://svmlight.joachims.org/ SVMlight]. The software also includes an interior point17 SVMQP is designed for largescale SVM problems. The underlying algorithm is an active set method for convext QPs. [http://www.research.ibm.com/people/k/katya/incas.pdf/ Here ] is the paper describing the algorithm and containing computational comparison with [http://svmlight.joachims.org/ SVMlight]. The software also includes an interior point 18 18 SVM solver which is designed for problems where Kernel matrix is (approximately) low rank. The program constructs the low 19 19 rank approximation and solves the approximate problem by the interior point method. The approximate solution can then be passed … … 38 38 }}} 39 39 where {{{K, \lambda}}} are positive scalars, {{{A}}} is a {{{p x p}}} symmetric matrix, {{{S}}} is a {{{p x p}}} nonnegative matrix and {{{C}}} is the unknown {{{p x p}}} 40 symmetric positive definite matrix. This software is written in C++ and has a Matlab interface which is provided. A brief description of how to use the code is available via 40 symmetric positive definite matrix. The '.*' notation stands for the elementwise product of two matrices and the  _1 is the sum of the absolute value of the elements of the matrix. 41 This software is written in C++ and has a Matlab interface which is provided. A brief description of how to use the code is available via 41 42 comments. A more detailed manual and the algorithm description is forthcoming. 42 43 