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https://link.springer.com/article/10.1023/A:1012427100071
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this paper through the...Cited by: 430
https://link.springer.com/content/pdf/10.1023%2FA%3A1012427100071.pdf
demonstrate the viability of the proposed method. Keywords: support vector machines, decomposition methods, classification 1. Introduction The support vector machine (SVM) is a new and promising technique for classification. Surveys of SVM are, for example, Vapnik (1995, 1998) and Sch¨olkopf, Burges, and Smola (1998). Given training vectors xCited by: 430
https://www.researchgate.net/publication/2612925_A_Simple_Decomposition_Method_for_Support_Vector_Machines
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets.
https://dl.acm.org/citation.cfm?id=599666
A Simple Decomposition Method for Support Vector Machines. Authors: Chih-Wei Hsu: Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, Republic of China. [email protected] Chih-Jen Lin:Cited by: 430
https://www.sciencedirect.com/science/article/pii/S0031320307000131
Support vector machines (SVMs) are a new and important tool in data classification. Recently much attention has been devoted to large scale data classifications where decomposition methods for SVMs play an important role. So far, several decomposition algorithms for SVMs have been proposed and applied in practice.Cited by: 6
https://www.researchgate.net/publication/220603810_A_simple_decomposition_algorithm_for_support_vector_machines_with_polynomial-time_convergence
Request PDF A simple decomposition algorithm for support vector machines with polynomial-time convergence Support vector machines (SVMs) are a new and important tool in data classification ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.1772
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The decomposition method is currently one of the major methods for solving support vector machines (SVM). Its convergence properties have not been fully understood. The general asymptotic convergence was first proposed by Chang et al. [2]. However, their working set selection does not coincide with existing ...
http://www.kernel-machines.org/publications/HsuLin99/?searchterm=svm
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this paper through the design of decomposition methods for bound-constrained SVM formulations we demonstrate that the working set selection is not a trivial task.
https://ieeexplore.ieee.org/document/857780/
The analysis of decomposition methods for support vector machines ... very few methods can handle the memory problem and an important one is the "decomposition method." However, there is no convergence proof so far. ... then show that this convergence proof is valid for general decomposition methods if their working set selection meets a simple ...Cited by: 224
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.4812
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this paper through the design of decomposition methods for bound-constrained SVM formulations we demonstrate that the working set selection is not a ...
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