- Referenced in 1043 articles
- LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this...
- Referenced in 257 articles
- 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 126 articles
- supports logistic regression and linear support vector machines. We provide easy-to-use command-line...
- Referenced in 66 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 95 articles
- machine learning models such as support vector machines, hidden Markov models, multiple kernel learning, linear...
- Referenced in 58 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...
- Referenced in 89 articles
- short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive...
- Referenced in 84 articles
- solving the optimization problem cast by Support Vector Machines (SVM). We prove that the number...
- Referenced in 81 articles
- 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...
- Referenced in 57 articles
- 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 49 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 44 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...
- Referenced in 54 articles
- unit and expression recognition, a linear support vector machine (SVM) classifier with leave...
- Referenced in 24 articles
- 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 43 articles
- response surfaces. Polynomial Chaos  and Support Vector Machine  are also possibilities and have...
- Referenced in 36 articles
- general sparse QPs, QPs arising from support vector machines, Huber regression problems, and QPs with...
- Referenced in 396 articles
- 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...
- Referenced in 28 articles
- Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning...
- Referenced in 24 articles
- programs that are not learnable by traditional machine learning methods. This explains the rapidly growing ... continuous internal states), feedforward networks and Support Vector Machines (no internal states...
- Referenced in 23 articles
- building on kernels, such as the support vector machine. It grew out of earlier pages...