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LIBOCAS - Library implementing Optimized Cutting Plane Algorithm (OCAS) solver for training linear SVM classifiers FEATURES - SVM solvers for training linear classifiers from large scale-data. - Binary (two-class) and genuine multi-class SVM formulations. - Optimized code written in C. - A stand alone application and MEX interface for Matlab. - Reads examples from SVM^light format. - Optimized for both sparse and dense features. - Parallelized version of the binary solver. - Allows using different C for each training example (Matlab's interace to binary solver). - Tools for classification. - Training translation invariant image classifiers from virtual examples. - Functions for computing image features based on Local Binary Patterns (LBP). PROBLEM FORMULATION OCAS solver is currently implemented for training binary (two-class) and multi-class SVM classifiers: 1. Binary case: OCAS solves the following unconstrained convex optimization task W^*,W0^* = argmin 0.5*(W'*W+W0^2) + C*sum max( 0, 1-y(i)*(W'*X(:,i)+W0*X0) ) W,W0 i=1:nData where C is the regularization constant, X [nDim x nData] are training feature vectors and y [nData x 1] are their binary labels (+1/-1). The result are parameters W^* [nDim x 1], W0^* [1 x 1] of the linear rule f(X) = sign( X'*W + W0 ) 2. Multi-class case: OCAS solves the following unconstrained convex optimization task W^* = argmin 0.5*sum_y (W(:,y)'*W(:,y)) + C* sum max( (y~=y(i)) + (W(:,y) - W(:,y(i)))'*X(:,i)) W i=1:nData y where C is the regularization constant, X [nDim x nData] are training feature vectors and y [nData x 1] are their labels from 1 to Y. The result are parameters W^* [nDim x Y] of the linear rule f(X) = argmax X'*W(:,y) y AVAILABILITY LIBOCAS can be downloaded from http://cmp.felk.cvut.cz/~xfrancv/ocas/html/index.html PLATFORMS GNU/Linux. LICENSE LIBOCAS is licensed under the GPL version 3 (cf. LICENSE). REFERENCES V. Franc, S. Sonnenburg. Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization. The Journal of Machine Learning Research (JMLR), vol. 10, pp. 2157--2192. October 2009. http://jmlr.csail.mit.edu/papers/volume10/franc09a/franc09a.pdf V. Franc, S. Sonnenburg. OCAS optimized cutting plane algorithm for Support Vector Machines. In Proceedings of ICML. Omnipress, 2008. http://cmp.felk.cvut.cz/~xfrancv/papers/Franc-OCAS-ICML08.pdf S. Sonnenburg, V. Franc. COFFIN: A Computational Framework for Linear SVMs. In Proceedings of the 27nd International Machine Learning Conference (ICML'10). Haifa 2010. http://cmp.felk.cvut.cz/~xfrancv/papers/Sonnenburg-COFFIN-ICML10.pdf