LIBSVM: a Library for Support Vector Machines

LIBSVM: a Library for Support Vector Machines (2001)

Cached

Download Links

[www.csie.ntu.edu.tw]
[www.csie.ntu.edu.tw]

Other Repositories/Bibliography

CiteULike

by Chih-chung Chang , Chih-Jen Lin

Citations:

2034 - 40 self

BibTeX

@MISC{Chang01libsvm:a,
    author = {Chih-chung Chang and Chih-Jen Lin},
    title = {LIBSVM: a Library for Support Vector Machines},
    year = {2001}
}

Years of Citing Articles

Bookmark

OpenURL

Abstract

LIBSVM is a library for support vector machines (SVM). Its goal is to help users can easily use SVM as a tool. In this document, we present all its implementation details. 1

Citations

6694	Statistical Learning Theory - Vapnik - 1998
1491	Support-vector networks - Cortes, Vapnik - 1995
1086	Making large-scale SVM learning practical - Joachims - 1999
933	A training algorithm for optimal margin classifiers - Boser, Guyon, et al. - 1992
758	JC: Fast Training of Support Vector Machines using Sequential Minimal Optimization - Platt - 1998
503	Probabilistic outputs for support vector machines and comparison to regularized likelihood methods - Platt - 1999
454	Training support vector machines: an application to face detection - Osuna, Freund, et al. - 1997
381	Estimating the support of a high-dimensional distribution - Schölkopf, Platt, et al. - 2001
369	A comparison of methods for multiclass support vector - Hsu
230	New support vector algorithms - Schölkopf, Smola, et al. - 2000
145	Support vector machines: Training and applications - Osuna, Freund, et al. - 1996
139	Improvements to platt’s SMO algorithm for SVM classifier design - Keerthi, Shevade, et al.
103	Another Approach to Polychotomous Classification - FRIEDMAN - 1996
94	Working set selection using the second order information for training SVM - Fan, Chen, et al. - 2005
79	A simple decomposition method for support vector machine - Hsu, Lin - 2002
63	A note on Platt’s probabilistic outputs for support vector machines - Lin, Lin, et al. - 2003
46	Pairwise Classification and Support Vector Machines - Kreßel - 1999
41	Convergence of a generalized SMO algorithm for SVM classifier design - Keerthi, Gilbert
41	Single-Layer Learning Revisited: a Stepwise Procedure for Building and Training a Neural Network - Knerr, Personnaz, et al. - 1990
38	Support vector machine: Reference manual - Saunders, Stitson, et al. - 1998
27	Training ν-support vector classifiers: Theory and algorithms - Chang, Lin - 2001
18	A geometric interpretation of ν-SVM classifiers - Crisp, Burges - 2000
14	A Study of SMO-Type Decomposition Methods for Support Vector Machines - Chen, Lin
12	Asymptotic convergence of an SMO algorithm without any assumptions - Lin - 2002
8	Large margin DAGS for multiclass classi - Platt, Cristianini, et al. - 2000
6	2001b). Training -support vector classi Theory and algorithms - Chang, Lin
5	Simple Probabilistic Predictions for Support Vector Regression,� in - Lin, Weng - 2004
3	Pairwise classi and support vector machines - Kreel - 1999
1	Training -support vector regression: Theory and algorithms - Chang - 2001
1	A geometric interpretation of -SVM classi - Burges - 1999
1	Another approach to polychotomous classi (Tech - Friedman - 1996
1	Simple probabilistic predictions for support vector regression - Burges, J - 1999