[PDF] Top 20 Decomposition methods for linear support vector machines
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Decomposition methods for linear support vector machines
... (Due to space limit, we discuss the difference of their implementations in [Z].) Thus, it is very difficult to conduct a fair comparison. Our goal here is only to demonstrate.. tha[r] ... See full document
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Decomposition Methods for Linear Support Vector Machines
... of Decomposition Methods for Lin- ear SVMs with n ¿ l The decomposition method is an iterative ...optimization methods which usually require the access of the whole Q, here, the memory ... See full document
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The analysis of decomposition methods for support vector machines
... of Decomposition Methods for Support Vector Machines Chih-Chung Chang, Chih-Wei Hsu, and Chih-Jen Lin Abstract—The support vector machine (SVM) is a new and ... See full document
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Linear Convergence of a Decomposition Method for Support Vector Machines
... used decomposition methods for support vector machines has been ...the linear convergence of a popular decomposition ... See full document
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A formal analysis of stopping criteria of decomposition methods for support vector machines
... of Decomposition Methods for Support Vector Machines Chih-Jen Lin, Member, IEEE Abstract—In a previous paper, we proved the convergence of a commonly used decomposition ... See full document
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A Simple Decomposition Method for Support Vector Machines
... both decomposition methods take many more iterations. For most problems we have tested, not only those presented here, we observe slow convergence of decomposition methods when C is ... See full document
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On the convergence of the decomposition method for support vector machines
... Its convergence properties have not been fully understood. The general asymptotic convergence was first proposed by Chang et al. However, their working set selection does not coincide with existing implementation. A ... See full document
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A note on the decomposition methods for support vector regression
... Technical report, Department of Computer Science and Information Engineering, National Taiwan University, 2000. On the convergence of the decomposi- tion method for support vec[r] ... See full document
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Reduction techniques for training support vector machines
... implementations for RSVM and compared them with two decomposition methods based on ...restricting support vectors from a randomly selected subset still downgrades the ...strategy. For ... See full document
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Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines-
... Abstract Linear support vector machines (SVM) are useful for classifying large-scale sparse ...algorithm for training linear SVM with the L2-loss ...art methods ... See full document
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LIBSVM: a Library for Support Vector Machines
... 4 Shrinking and Caching 4.1 Shrinking Since for many problems the number of free support vectors (i.e. 0 < α i < C) is small, the shrinking technique reduces the size of the working problem without ... See full document
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Support Vector Machines for Mandarin Phonetic Morse Code Recognition
... rehabilitation for people with various neuromuscular diseases, such as amyotrophic lateral sclerosis, multiple sclerosis, and muscular ...rate for persons with severe ...two methods, support ... See full document
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Incremental Reduced Support Vector Machines
... Recently, support vector machines (SVMs) with linear or nonlinear kernels [1], [2], [16] have become the most promising learning al- gorithm for classification as well as regression ... See full document
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A Parallelized Learning Algorithm for Monotonicity Constrained Support Vector Machines
... generating vector sequences of iterates, residuals corresponding to iterates, and search directions used in updating iterates and ...the vector sequences satisfy certain orthogonality ...definite ... See full document
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A Guide to Support Vector Machines
... use methods which avoid doing an exhaustive parameter search by approximations or ...advanced methods since there are only two ...advanced methods are iterative processes, ... See full document
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Radius Margin Bounds for Support Vector Machines with the RBF Kernel
... Gradient Methods Experiments in the previous section have shown the viability of some possi- ble bounds for ...optimization methods. These methods iteratively find a descent direction p by ... See full document
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A study of reduced support vector machines
... as support vectors and solves a smaller optimization ...yet. For example, we do not know if it possesses com- parable generalization ability as the standard ...see for how large problems RSVM ... See full document
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Working Set Selection Using Second Order Information for Training Support Vector Machines
... iteration, for difficult problems, the decom- position method suffers from slow ...Better methods of working set selection could reduce the number of iterations and hence are an important research ... See full document
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Adaptive Morse code recognition using support vector machines for persons with physical disabilities
... device for persons whose hand coordination and dexterity are im- paired by such ailments as amyotrophic lateral sclerosis, multiple sclerosis, muscular dystrophy, and other severe ...signal for a defined ... See full document
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Analysis of Switching Dynamics with Competing Support Vector Machines
... a linear system, sometimes a direct method such as Gaussian elimination is ...iterative methods using the steepest descent direction are considered. For the modified form of ... See full document
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