-
1
-
-
0003450542
-
-
Zhang X.(transl.), Beijing: Tsinghua University Press, Chinese source
-
Vapnik V. The Nature of Statistical Learning Theory [M]. ZHANG Xuegong. Beijing: Tsinghua University Press, 2000. (in Chinese)
-
(2000)
The Nature of Statistical Learning Theory
-
-
Vapnik, V.1
-
2
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
Burges C. A tutorial on support vector machines for pattern recognition [J]. Data Mining and Knowledge Discovery, 1998, 2(2): 1-43.
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.2
, pp. 1-43
-
-
Burges, C.1
-
3
-
-
0001907967
-
Support vector machines: Hype or hallelujah
-
Bennett K, Campbell C. Support vector machines: hype or hallelujah? [J]. SIGKDD Explorations, 2000, 2(2): 1-13.
-
(2000)
SIGKDD Explorations
, vol.2
, Issue.2
, pp. 1-13
-
-
Bennett, K.1
Campbell, C.2
-
4
-
-
0033640690
-
A fast iterative nearest point algorithm for support vector machine classifier design
-
Keerthi S, Shevade S, Bhattcharyya C, et al. A fast iterative nearest point algorithm for support vector machine classifier design [J]. IEEE Transactions on Neural Network, 2000, 11(1): 124-136.
-
(2000)
IEEE Transactions on Neural Network
, vol.11
, Issue.1
, pp. 124-136
-
-
Keerthi, S.1
Shevade, S.2
Bhattcharyya, C.3
-
5
-
-
0035242302
-
The theory of SVM and programming based algorithms in neural networks
-
Chinese source
-
ZHANG Ling. The theory of SVM and programming based algorithms in neural networks [J]. Chinese Journal of Computers, 2001, 24(2), 113-118. (in Chinese)
-
(2001)
Chinese Journal of Computers
, vol.24
, Issue.2
, pp. 113-118
-
-
Zhang, L.1
-
6
-
-
0000222692
-
Formulations of support vector machines: A note from an optimization point of view
-
LIN Chihjen. Formulations of support vector machines: a note from an optimization point of view [J]. Neural Computation, 2001, 13(2): 307-317.
-
(2001)
Neural Computation
, vol.13
, Issue.2
, pp. 307-317
-
-
Lin, C.1
-
7
-
-
0004322633
-
Simple learning algorithm for training support vector machines
-
Technical Report CIG-TR-KA, Bristol, UK: University of Bristol, Engineering Mathematics, Computational Intelligence Group
-
Campbell C, Cristianini N. Simple Learning Algorithm for Training Support Vector Machines [R]. Technical Report CIG-TR-KA, Bristol, UK: University of Bristol, Engineering Mathematics, Computational Intelligence Group, 1999.
-
(1999)
-
-
Campbell, C.1
Cristianini, N.2
-
9
-
-
0003425662
-
Support vector machines: Training and application
-
CBCL Paper # 144/AI Memo #1602, Cambridge, MA: Massachusetts Institute of Technology, AI Lab
-
Osuna E, Freund R. Girosi F. Support Vector Machines: Training and Application [R]. CBCL Paper # 144/AI Memo #1602, Cambridge, MA: Massachusetts Institute of Technology, AI Lab, 1997.
-
(1997)
-
-
Osuna, E.1
Freund, R.2
Girosi, F.3
-
10
-
-
0031334889
-
An improved training algorithm for support vector machines
-
Principe J., Gile L. and Morgan N. (ed.), IEEE
-
Osuna E, Freund R, Girosi F. An improved training algorithm for support vector machines [A]. Principe J, Gile L, Morgan N, et al. Proceedings of the 1997 IEEE Workshop on Neural Networks for Signal Processing [C]. IEEE, 1997. 276-285.
-
(1997)
Proceedings of the 1997 IEEE Workshop on Neural Networks for Signal Processing
, pp. 276-285
-
-
Osuna, E.1
Freund, R.2
Girosi, F.3
-
11
-
-
0002714543
-
Making large-scale support vector machine learning practical
-
Scholkopf B., Burges C. and Smola A., (ed.), Cambridge, MA: MIT Press
-
Joachims T. Making large-scale support vector machine learning practical [A]. Scholkopf B, Burges C, Smola A. Advances in Kernel Methods - Support Vector Learning [C]. Cambridge, MA: MIT Press, 1999. 169-184
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 169-184
-
-
Joachims, T.1
-
12
-
-
0035506741
-
On the convergence of the decomposition method for support vector machines
-
LIN Chihjen. On the convergence of the decomposition method for support vector machines [J]. IEEE Transactions on Neural Network, 2001, 12(6): 1288-1298.
-
(2001)
IEEE Transactions on Neural Network
, vol.12
, Issue.6
, pp. 1288-1298
-
-
Lin, C.1
-
13
-
-
84898947865
-
An improved decomposition algorithm for regression support vector machines
-
Solla S., Leen T. and Muller K.-R.(ed.), Cambridge, MA: MIT Press
-
Laskov P. An improved decomposition algorithm for regression support vector machines [A]. Solla S, Leen T, Muller K-R. Advances in Neural Information Processing Systems 12 [C]. Cambridge, MA: MIT Press, 2000. 484-490.
-
(2000)
Advances in Neural Information Processing Systems 12
, pp. 484-490
-
-
Laskov, P.1
-
14
-
-
0036158636
-
Feasible direction decomposition algorithms for training support vector machines
-
Laskov P. Feasible direction decomposition algorithms for training support vector machines [J]. Machine Learning, 2002, 46(l/3): 315-349.
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 315-349
-
-
Laskov, P.1
-
15
-
-
84898970330
-
Fast training of support vector classifiers
-
Leen T., Dietterich T. and Tresp V.(ed.), Cambridge, MA: MIT Press
-
Pérez-Cruz F, Alarcon-Diana P, Navia-Vazquez A, et al. Fast training of support vector classifiers [A]. Leen T, Dietterich T, Tresp V. Advances in Neural Information Processing Systems 13 [C]. Cambridge, MA: MIT Press, 2001. 734-740.
-
(2001)
Advances in Neural Information Processing Systems 13
, pp. 734-740
-
-
Pérez-Cruz, F.1
Alarcon-Diana, P.2
Navia-Vazquez, A.3
-
16
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
Scholkopf B., Burges C. and Smola A., Cambridge, MA: MIT Press
-
Platt J. Fast training of support vector machines using sequential minimal optimization [A]. Scholkopf B, Burges C, Smola A. Advances in Kernel Methods - Support Vector Learning [C]. Cambridge, MA: MIT Press, 1999. 185-208.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 185-208
-
-
Platt, J.1
-
17
-
-
84898983292
-
Using analytic QP and sparseness to speed training of support vector machines
-
Kearns M., Solla S. and Cohn D. (ed.), Cambridge, MA: MIT Press
-
Platt J. Using analytic QP and sparseness to speed training of support vector machines [A]. Kearns M, Solla S, Cohn D. Advances in Neural Information Processing Systems 11 [C]. Cambridge, MA: MIT Press, 1999. 557-563.
-
(1999)
Advances in Neural Information Processing Systems 11
, pp. 557-563
-
-
Platt, J.1
-
18
-
-
0036160859
-
Efficient SVM regression training with SMO
-
Flake G, Lwarence S. Efficient SVM regression training with SMO [J]. Machine Learning, 2002, 46 (1/3): 271-290.
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 271-290
-
-
Flake, G.1
Lwarence, S.2
-
19
-
-
0000545946
-
Improvements to Platt's SMO algorithm for SVM classifier design
-
Keerthi S, Shevade S, Bhattcharyya C, et al. Improvements to Platt's SMO algorithm for SVM classifier design [J]. Neural Computation, 2001, 13 (3): 637-649.
-
(2001)
Neural Computation
, vol.13
, Issue.3
, pp. 637-649
-
-
Keerthi, S.1
Shevade, S.2
Bhattcharyya, C.3
-
20
-
-
0036163654
-
Convergence of a generalized SO algorithm for SVM classifier design
-
Keerthi S, Gilbert E. Convergence of a generalized SO algorithm for SVM classifier design [J]. Machine Learning. 2002, 46 (1/3): 351-360.
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 351-360
-
-
Keerthi, S.1
Gilbert, E.2
-
21
-
-
0003710380
-
LIBSVM: A library for support vector machines (Version 2.3)
-
CHANG Chihchung, LIN Chihjen. LIBSVM: a Library for Support Vector Machines (Version 2.3) [EB/OL]. http://www.csie.ntu.edu.tw/-cjlin/papers/libsvm.pdf, 2001-06-08.
-
(2001)
-
-
Chang, C.1
Lin, C.2
-
22
-
-
0005811184
-
Polynomial-time decomposition algorithms for support vector machines
-
LANL Technical Report LA-UR-00-3800, Los Alamos: Los Alamos National Laboratory
-
Hush D, Scovel C. Polynomial-Time Decomposition Algorithms for Support Vector Machines [R]. LANL Technical Report LA-UR-00-3800, Los Alamos: Los Alamos National Laboratory, 2000.
-
(2000)
-
-
Hush, D.1
Scovel, C.2
-
25
-
-
0038517617
-
Asymptotic convergence of an SMO algorithm without any assumptions
-
LIN Chihjen. Asymptotic convergence of an SMO algorithm without any assumptions [EB/OL]. http://www.csie.ntu.edu.tw/-cjlin/papers/q2conv.pdf, 2001-12-01.
-
(2001)
-
-
Lin, C.1
-
26
-
-
0038178786
-
Linear convergence of a decomposition method for support vector machines
-
LIN Chihjen. Linear convergence of a decomposition method for support vector machines [EB/OL]. http://www.csie.ntu.edu.tw/-cjlin/papers/linearconv.pdf, 2001-12-01.
-
(2001)
-
-
Lin, C.1
-
27
-
-
0000913324
-
VMTorch: A support vector machine for large-scale regression and classification problems
-
Collobert R. Bengio S. SVMTorch: a support vector machine for large-scale regression and classification problems [J]. Journal of Machine Learning Research, 2001, 1: 143-160.
-
(2001)
Journal of Machine Learning Research
, vol.1
, pp. 143-160
-
-
Collobert, R.1
Bengio, S.2
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