-
1
-
-
0026966646
-
-
Bernhard E. Boser, Isabelle M. Guyon, Vladimir N. Vapnik, A training algorithm for optimal margin classifiers, in: Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, 1992, pp. 144-152
-
-
-
-
2
-
-
0033879594
-
Approximation algorithms for knapsack problems with cardinality constraints
-
Caprara A., Kellerer H., Pferschy U., and Pisinger D. Approximation algorithms for knapsack problems with cardinality constraints. European Journal of Operational Research 123 2 (2000) 333-345
-
(2000)
European Journal of Operational Research
, vol.123
, Issue.2
, pp. 333-345
-
-
Caprara, A.1
Kellerer, H.2
Pferschy, U.3
Pisinger, D.4
-
4
-
-
34547832529
-
-
Chih-Chung Chang, Chih-Jen Lin, LIBSVM: A library for support vector machines, 2001. Available from: http://www.csie.ntu.edu.tw/~cjlin/libsvm
-
-
-
-
5
-
-
33646521266
-
-
Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin, Training support vector machines via SMO-type decomposition methods, in: Proceedings of the 16th International Conference on Algorithmic Learning Theory, 2005, pp. 45-62
-
-
-
-
6
-
-
33746932071
-
A study on SMO-type decomposition methods for support vector machines
-
Chen P.-H., Fan R.-E., and Lin C.-J. A study on SMO-type decomposition methods for support vector machines. IEEE Transactions on Neural Networks 17 4 (2006) 893-908
-
(2006)
IEEE Transactions on Neural Networks
, vol.17
, Issue.4
, pp. 893-908
-
-
Chen, P.-H.1
Fan, R.-E.2
Lin, C.-J.3
-
7
-
-
0036158552
-
A simple decomposition method for support vector machines
-
Hsu C.-W., and Lin C.-J. A simple decomposition method for support vector machines. Machine Learning 46 1-3 (2002) 291-314
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 291-314
-
-
Hsu, C.-W.1
Lin, C.-J.2
-
9
-
-
0037399781
-
Polynomial-time decomposition algorithms for support vector machines
-
Hush D., and Scovel C. Polynomial-time decomposition algorithms for support vector machines. Machine Learning 51 1 (2003) 51-71
-
(2003)
Machine Learning
, vol.51
, Issue.1
, pp. 51-71
-
-
Hush, D.1
Scovel, C.2
-
10
-
-
0016560084
-
Fast approximation algorithms for knapsack and sum of subset problem
-
Ibarra O.H., and Kim C.E. Fast approximation algorithms for knapsack and sum of subset problem. Journal of the Association on Computing Machinery 22 4 (1975) 463-468
-
(1975)
Journal of the Association on Computing Machinery
, vol.22
, Issue.4
, pp. 463-468
-
-
Ibarra, O.H.1
Kim, C.E.2
-
11
-
-
0002714543
-
Making large scale SVM learning practical
-
Schölkopf B., Burges C.J.C., and Smola A.J. (Eds), MIT Press
-
Joachims T. Making large scale SVM learning practical. In: Schölkopf B., Burges C.J.C., and Smola A.J. (Eds). Advances in Kernel Methods-Support Vector Learning (1998), MIT Press 169-184
-
(1998)
Advances in Kernel Methods-Support Vector Learning
, pp. 169-184
-
-
Joachims, T.1
-
12
-
-
0003037529
-
Reducibility among combinatorial problems
-
Miller R.E., and Thatcher J.W. (Eds), Plenum Press
-
Karp R.M. Reducibility among combinatorial problems. In: Miller R.E., and Thatcher J.W. (Eds). Complexity of Computer Computations (1972), Plenum Press 85-103
-
(1972)
Complexity of Computer Computations
, pp. 85-103
-
-
Karp, R.M.1
-
13
-
-
0036163654
-
Convergence of a generalized SMO algorithm for SVM classifier design
-
Sathiya Keerthi S., and Gilbert E.G. Convergence of a generalized SMO algorithm for SVM classifier design. Machine Learning 46 1-3 (2002) 351-360
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 351-360
-
-
Sathiya Keerthi, S.1
Gilbert, E.G.2
-
14
-
-
0034271493
-
Improvements to SMO algorithm for SVM regression
-
Sathiya Keerthi S., Shevade S., Bhattacharyya C., and Murthy K.R.K. Improvements to SMO algorithm for SVM regression. IEEE Transactions on Neural Networks 11 5 (2000) 1188-1193
-
(2000)
IEEE Transactions on Neural Networks
, vol.11
, Issue.5
, pp. 1188-1193
-
-
Sathiya Keerthi, S.1
Shevade, S.2
Bhattacharyya, C.3
Murthy, K.R.K.4
-
15
-
-
0000545946
-
Improvements to Platt's SMO algorithm for SVM classifier design
-
Sathiya Keerthi S., Shevade S.K., Bhattacharyya C., and Murthy K.R.K. Improvements to Platt's SMO algorithm for SVM classifier design. Neural Computation 13 3 (2001) 637-649
-
(2001)
Neural Computation
, vol.13
, Issue.3
, pp. 637-649
-
-
Sathiya Keerthi, S.1
Shevade, S.K.2
Bhattacharyya, C.3
Murthy, K.R.K.4
-
16
-
-
0012792757
-
On the existence of fast approximation schemes
-
Mangasarian O.L., Meyer R.R., and Robinson S.M. (Eds), Academic Press
-
Korte B., and Schrader R. On the existence of fast approximation schemes. In: Mangasarian O.L., Meyer R.R., and Robinson S.M. (Eds). Nonlinear Programming vol. 4 (1981), Academic Press 415-437
-
(1981)
Nonlinear Programming
, vol.4
, pp. 415-437
-
-
Korte, B.1
Schrader, R.2
-
17
-
-
0036158636
-
Feasible direction decomposition algorithms for training support vector machines
-
Laskov P. Feasible direction decomposition algorithms for training support vector machines. Machine Learning 46 1-3 (2002) 315-349
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 315-349
-
-
Laskov, P.1
-
18
-
-
0040081684
-
A note on the decomposition methods for support vector regression
-
Liao S.-P., Lin H.-T., and Lin C.-J. A note on the decomposition methods for support vector regression. Neural Computation 14 6 (2002) 1267-1281
-
(2002)
Neural Computation
, vol.14
, Issue.6
, pp. 1267-1281
-
-
Liao, S.-P.1
Lin, H.-T.2
Lin, C.-J.3
-
19
-
-
34547847632
-
-
Chih-Jen Lin, Linear convergence of a decomposition method for support vector machines, 2001. Available from: http://www.csie.ntu.edu.tw/~cjlin/papers/linearconv.pdf
-
-
-
-
20
-
-
0035506741
-
On the convergence of the decomposition method for support vector machines
-
Lin C.-J. On the convergence of the decomposition method for support vector machines. IEEE Transactions on Neural Networks 12 6 (2001) 1288-1298
-
(2001)
IEEE Transactions on Neural Networks
, vol.12
, Issue.6
, pp. 1288-1298
-
-
Lin, C.-J.1
-
21
-
-
0036129250
-
Asymptotic convergence of an SMO algorithm without any assumptions
-
Lin C.-J. Asymptotic convergence of an SMO algorithm without any assumptions. IEEE Transactions on Neural Networks 13 1 (2002) 248-250
-
(2002)
IEEE Transactions on Neural Networks
, vol.13
, Issue.1
, pp. 248-250
-
-
Lin, C.-J.1
-
22
-
-
0036737295
-
A formal analysis of stopping criteria of decomposition methods for support vector machines
-
Lin C.-J. A formal analysis of stopping criteria of decomposition methods for support vector machines. IEEE Transactions on Neural Networks 13 5 (2002) 1045-1052
-
(2002)
IEEE Transactions on Neural Networks
, vol.13
, Issue.5
, pp. 1045-1052
-
-
Lin, C.-J.1
-
23
-
-
34547836536
-
-
Nikolas List, Personal communication
-
-
-
-
24
-
-
22944453692
-
-
Nikolas List, Convergence of a generalized gradient selection approach for the decomposition method, in: Proceedings of the 15th International Conference on Algorithmic Learning Theory, 2004, pp. 338-349
-
-
-
-
25
-
-
9444296042
-
-
Nikolas List, Hans Ulrich Simon, A general convergence theorem for the decomposition method, in: Proceedings of the 17th Annual Conference on Computational Learning Theory, 2004, pp. 363-377
-
-
-
-
26
-
-
26944489027
-
-
Nikolas List, Hans Ulrich Simon, General polynomial time decomposition algorithms, in: Proceedings of the 17th Annual Conference on Computational Learning Theory, 2005, pp. 308-322
-
-
-
-
30
-
-
0030673582
-
-
Edgar E. Osuna, Robert Freund, Federico Girosi, Training support vector machines: An application to face detection, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1997, pp. 130-136
-
-
-
-
31
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
Schölkopf B., Burges C.J.C., and Smola A.J. (Eds), MIT Press
-
Platt J.C. Fast training of support vector machines using sequential minimal optimization. In: Schölkopf B., Burges C.J.C., and Smola A.J. (Eds). Advances in Kernel Methods-Support Vector Learning (1998), MIT Press 185-208
-
(1998)
Advances in Kernel Methods-Support Vector Learning
, pp. 185-208
-
-
Platt, J.C.1
-
32
-
-
34547836532
-
-
Craig Saunders, Mark O. Stitson, Jason Weston, Leon Bottou, Bernhard Schölkopf, Alexander J. Smola, Support vector machine reference manual, Technical Report CSD-TR-98-03, Royal Holloway, University of London, Egham, UK, 1998
-
-
-
-
33
-
-
22944492712
-
-
Hans Ulrich Simon, On the complexity of working set selection, in: Proceedings of the 15th International Conference on Algorithmic Learning Theory, 2004, pp. 324-337
-
-
-
|