-
1
-
-
0242288816
-
A geometric approach to support vector regression
-
Bi J, Bennett KP (2003) A geometric approach to support vector regression. Neurocomputing 55: 79-108.
-
(2003)
Neurocomputing
, vol.55
, pp. 79-108
-
-
Bi, J.1
Bennett, K.P.2
-
4
-
-
0346250790
-
Practical selection of SVM parameters and noise estimation for SVM regression
-
Cherkassky V, Ma YQ (2004) Practical selection of SVM parameters and noise estimation for SVM regression. Neural Netw 17: 113-126.
-
(2004)
Neural Netw
, vol.17
, pp. 113-126
-
-
Cherkassky, V.1
Ma, Y.Q.2
-
7
-
-
29644438050
-
Statistical comparisons of classifiers over multiple data sets
-
Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7: 1-30.
-
(2006)
J Mach Learn Res
, vol.7
, pp. 1-30
-
-
Demšar, J.1
-
9
-
-
69249202291
-
Newton's method for nonparallel plane proximal classifier with unity norm hyperplanes
-
Ghorai S, Hossain SJ, Mukherjee A, Dutta PK (2010) Newton's method for nonparallel plane proximal classifier with unity norm hyperplanes. Signal Proc 90: 93-104.
-
(2010)
Signal Proc
, vol.90
, pp. 93-104
-
-
Ghorai, S.1
Hossain, S.J.2
Mukherjee, A.3
Dutta, P.K.4
-
11
-
-
0002714543
-
Making large-scale SVM learning practical
-
B. Schölkopf, C. J. C. Burges, and A. J. Smola (Eds.), Cambridge: MIT Press
-
Joachims T (1999) Making large-scale SVM learning practical. In: Schölkopf B, Burges CJC, Smola AJ (eds) Advances in Kernel methods-support vector learning. MIT Press, Cambridge, pp 169-184.
-
(1999)
Advances in Kernel Methods-Support Vector Learning
, pp. 169-184
-
-
Joachims, T.1
-
12
-
-
34248636293
-
Fast sparse approximation for least squares support vector machine
-
Jiao L, Bo L, Wang L (2007) Fast sparse approximation for least squares support vector machine. IEEE Trans Neural Netw 18(3): 685-697.
-
(2007)
IEEE Trans Neural Netw
, vol.18
, Issue.3
, pp. 685-697
-
-
Jiao, L.1
Bo, L.2
Wang, L.3
-
13
-
-
0000545946
-
Improvements to Platt's SMO algorithm for SVM classifier design
-
Keerthi SS, Shevade SK, Bhattacharyya C, Murthy K (2001) Improvements to Platt's SMO algorithm for SVM classifier design. Neural Comput 13(3): 637-649.
-
(2001)
Neural Comput
, vol.13
, Issue.3
, pp. 637-649
-
-
Keerthi, S.S.1
Shevade, S.K.2
Bhattacharyya, C.3
Murthy, K.4
-
14
-
-
0037313407
-
SMO algorithm for least squares SVM formulations
-
Keerthi SS, Shevade SK (2003) SMO algorithm for least squares SVM formulations. Neural Comput 15(2): 487-507.
-
(2003)
Neural Comput
, vol.15
, Issue.2
, pp. 487-507
-
-
Keerthi, S.S.1
Shevade, S.K.2
-
15
-
-
48649097170
-
Application of smoothing technique on twin support vector machines
-
Kumar MA, Gopal M (2008) Application of smoothing technique on twin support vector machines. Pattern Recogn Lett 29: 1842-1848.
-
(2008)
Pattern Recogn Lett
, vol.29
, pp. 1842-1848
-
-
Kumar, M.A.1
Gopal, M.2
-
16
-
-
60249095678
-
Least squares twin support vector machines for pattern classification
-
Kumar MA, Gopal M (2009) Least squares twin support vector machines for pattern classification. Expert Syst Appl 36: 7535-7543.
-
(2009)
Expert Syst Appl
, vol.36
, pp. 7535-7543
-
-
Kumar, M.A.1
Gopal, M.2
-
17
-
-
0037507242
-
Pruning error minimization in least squares support vector machines
-
Kruif BJ, Vries A (2004) Pruning error minimization in least squares support vector machines. IEEE Trans Neural Netw 14(3): 696-702.
-
(2004)
IEEE Trans Neural Netw
, vol.14
, Issue.3
, pp. 696-702
-
-
Kruif, B.J.1
Vries, A.2
-
18
-
-
19944407892
-
e{open}-SSVR: A smooth support vector machine fore{open} -insensitive regression
-
Lee Y-J, Hsieh W-F, Huang C-M (2005) e{open}-SSVR: a smooth support vector machine fore{open} -insensitive regression. IEEE Trans Knowl Data Eng 17(5): 678-685.
-
(2005)
IEEE Trans Knowl Data Eng
, vol.17
, Issue.5
, pp. 678-685
-
-
Lee, Y.-J.1
Hsieh, W.-F.2
Huang, C.-M.3
-
19
-
-
33644830072
-
Multisurface proximal support vector classification via generalized eigenvalues
-
Mangasarian OL, Wild EW (2006) Multisurface proximal support vector classification via generalized eigenvalues. IEEE Trans Pattern Anal Mach Intell 28(1): 69-74.
-
(2006)
IEEE Trans Pattern Anal Mach Intell
, vol.28
, Issue.1
, pp. 69-74
-
-
Mangasarian, O.L.1
Wild, E.W.2
-
20
-
-
33745801137
-
Exact 1-norm support vector machine via unconstrained convex differentiable minimization
-
Mangasarian OL (2006) Exact 1-norm support vector machine via unconstrained convex differentiable minimization. J Mach Learn Res 7: 1517-1530.
-
(2006)
J Mach Learn Res
, vol.7
, pp. 1517-1530
-
-
Mangasarian, O.L.1
-
21
-
-
0031334889
-
An improved training algorithm for support vector machines
-
In: Principe J, Gile L, Morgan N, Wilson E (eds), IEEE
-
Osuna E, Freund R, Girosi F (1997) An improved training algorithm for support vector machines. In: Principe J, Gile L, Morgan N, Wilson E (eds) Neural networks for signal processing VII-proceedings of the 1997 IEEE workshop. IEEE. pp 276-285.
-
(1997)
Neural networks for signal processing VII-proceedings of the 1997 IEEE workshop
, pp. 276-285
-
-
Osuna, E.1
Freund, R.2
Girosi, F.3
-
23
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
B. Schölkopf, C. J. C. Burges, and A. J. Smola (Eds.), Cambridge: MIT Press
-
Platt JC (1999) Fast training of support vector machines using sequential minimal optimization. In: Schölkopf B, Burges CJC, Smola AJ (eds) Advances in kernel methods-support vector learning. MIT Press, Cambridge, pp 185-208.
-
(1999)
Advances in Kernel Methods-Support Vector Learning
, pp. 185-208
-
-
Platt, J.C.1
-
24
-
-
0034271493
-
Improvements to the SMO algorithm for SVM regression
-
Shevade SK, Keerthi SS, Bhattacharyya C, Murthy KRK (2000) Improvements to the SMO algorithm for SVM regression. IEEE Trans Neural Netw 11(5): 1188-1193.
-
(2000)
IEEE Trans Neural Netw
, vol.11
, Issue.5
, pp. 1188-1193
-
-
Shevade, S.K.1
Keerthi, S.S.2
Bhattacharyya, C.3
Murthy, K.R.K.4
-
25
-
-
0032638628
-
Least squares support vector machine classifiers
-
Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Proc Lett 9(3): 293-300.
-
(1999)
Neural Proc Lett
, vol.9
, Issue.3
, pp. 293-300
-
-
Suykens, J.A.K.1
Vandewalle, J.2
-
26
-
-
0037695279
-
-
Singapore: World Scientific
-
Suykens JAK, Gestel T, Brabanter J, Moor B, Vandewalle J (2002) Least squares support vector machines. World Scientific, Singapore.
-
(2002)
Least Squares Support Vector Machines
-
-
Suykens, J.A.K.1
Gestel, T.2
Brabanter, J.3
Moor, B.4
Vandewalle, J.5
-
29
-
-
10244219830
-
A heuristic training for support vector regression
-
Wang W, Xu Z (2004) A heuristic training for support vector regression. Neurocomputing 61: 259-275.
-
(2004)
Neurocomputing
, vol.61
, pp. 259-275
-
-
Wang, W.1
Xu, Z.2
-
30
-
-
28244453270
-
SMO-based pruning methods for sparse least squares support vector machines
-
Zeng XY, Chen XW (2005) SMO-based pruning methods for sparse least squares support vector machines. IEEE Trans Neural Netw 16(6): 1541-1546.
-
(2005)
IEEE Trans Neural Netw
, vol.16
, Issue.6
, pp. 1541-1546
-
-
Zeng, X.Y.1
Chen, X.W.2
-
31
-
-
58249091399
-
Recursive reduced least squares support vector regression
-
Zhao Y, Sun J (2009) Recursive reduced least squares support vector regression. Pattern Recogn 42: 837-842.
-
(2009)
Pattern Recogn
, vol.42
, pp. 837-842
-
-
Zhao, Y.1
Sun, J.2
|