- Referenced in 615 articles
- LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this...
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- implementation of Vapnik’s Support Vector Machine [Vapnik, 1995] for the problem of pattern recognition ... handle problems with many thousands of support vectors efficiently. The software also provides methods...
- Referenced in 56 articles
- SVMTorch: Support vector machines for large-scale regression problems. Support Vector Machines (SVMs) for regression ... Joachims [“Making large-scale support vector machine learning practical”, in: B. Schölkopf, C. Burges ... convergence of the decomposition method for support vector machines (Tech. Rep.). National Taiwan University...
- Referenced in 45 articles
- SSVM: A smooth support vector machine for classification. Smoothing methods, extensively used for solving important ... unconstrained smooth reformulation of the support vector machine for pattern classification using a completely arbitrary ... term such reformulation a Smooth Support Vector Machine (SSVM). A fast Newton-Armijo algorithm ... Joachims, in: Advances in kernel methods – support vector learning, MIT Press: Cambridge...
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- machine learning models such as support vector machines, hidden Markov models, multiple kernel learning, linear...
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- supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning ... scale problems, by iteratively using existing support vector machine code. However, it turns out that...
- Referenced in 36 articles
- RSVM: Reduced Support Vector Machines. An algorithm is proposed which generates a nonlinear kernel-based ... test set correctness for the reduced support vector machine (RSVM), with a nonlinear separating surface ... better than that of a conventional support vector machine (SVM) with a nonlinear surface that...
- Referenced in 55 articles
- supports logistic regression and linear support vector machines. We provide easy-to-use command-line...
- Referenced in 31 articles
- Parallel software for training large scale support vector machines on multiprocessor systems Parallel software ... quadratic program arising in training support vector machines for classification problems is introduced. The software ... software makes large scale standard nonlinear support vector machines effectively tractable on common multiprocessor systems...
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- unit and expression recognition, a linear support vector machine (SVM) classifier with leave...
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- solving the optimization problem cast by Support Vector Machines (SVM). We prove that the number...
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- Kernel-based Machine Learning Lab. Kernel-based machine learning methods for classification, regression, clustering, novelty ... reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes...
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- matlab/c toolbox for least squares support vector machines. Support Vector Machines is a powerful methodology ... problems, typically quadratic programs. Least Squares Support Vector Machines (LS-SVM) are reformulations...
- Referenced in 27 articles
- short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive...
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- computers and networks of workstations supporting parallel virtual machine (PVM) and/or message passing interface ... designed and produced analogous software for workstations, vector supercomputers, and shared memory parallel computers. Both...
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- general sparse QPs, QPs arising from support vector machines, Huber regression problems, and QPs with...
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- Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning...
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- building on kernels, such as the support vector machine. It grew out of earlier pages...
- Referenced in 14 articles
- unsupervised machine learning algorithms, including support vector machines (SVMs), boosted and bagged decision trees...
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- MATLAB Support Vector Machine Toolbox. This is a beta version of a MATLAB toolbox implementing ... Vapnik’s support vector machine, as described in . Training is performed using ... started. For a good introduction to support vector machines, see the excellent book by Cristianini ... kernel evaluations for efficiency. Support for multi-class support vector classification using max wins, pairwise...