-
4
-
-
0015000439
-
Some results on Tchebycheffian spline functions
-
G. Kimeldorf, and G. Wahba Some results on Tchebycheffian spline functions J. Math. Anal. Appl. 33 1971 82 95
-
(1971)
J. Math. Anal. Appl.
, vol.33
, pp. 82-95
-
-
Kimeldorf, G.1
Wahba, G.2
-
5
-
-
0003408420
-
-
MIT Press Cambridge, MA
-
B. Schölkopf, and A. Smola Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond 2002 MIT Press Cambridge, MA
-
(2002)
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and beyond
-
-
Schölkopf, B.1
Smola, A.2
-
10
-
-
80052955921
-
A review of optimization methodologies in support vector machines
-
J. Shawe-Taylor, and S. Sun A review of optimization methodologies in support vector machines Neurocomputing 74 17 2011 3609 3618
-
(2011)
Neurocomputing
, vol.74
, Issue.17
, pp. 3609-3618
-
-
Shawe-Taylor, J.1
Sun, S.2
-
11
-
-
17644439852
-
A robust support vector algorithm for nonparametric spectral analysis
-
J.L. Rojo-Álvarez, M. Martínez-Ramón, A.R. Figueiras-Vidal, A. García-Armada, and A. Artés-Rodríguez A robust support vector algorithm for nonparametric spectral analysis IEEE Signal Process. Lett. 10 2003 320 323
-
(2003)
IEEE Signal Process. Lett.
, vol.10
, pp. 320-323
-
-
Rojo-Álvarez, J.L.1
Martínez-Ramón, M.2
Figueiras-Vidal, A.R.3
García-Armada, A.4
Artés-Rodríguez, A.5
-
12
-
-
9144233003
-
Support vector method for robust ARMA system identification
-
J.L. Rojo-Álvarez, M. Martínez-Ramón, M. de Prado-Cumplido, A. Artés-Rodríguez, and A.R. Figueiras-Vidal Support vector method for robust ARMA system identification IEEE Trans. Signal Proces. 52 2004 155 164
-
(2004)
IEEE Trans. Signal Proces.
, vol.52
, pp. 155-164
-
-
Rojo-Álvarez, J.L.1
Martínez-Ramón, M.2
De Prado-Cumplido, M.3
Artés-Rodríguez, A.4
Figueiras-Vidal, A.R.5
-
13
-
-
27744526773
-
Support vector machines framework for linear signal processing
-
J.L. Rojo-Álvarez, G. Camps-Valls, M. Martínez-Ramón, E. Soria-Olivas, Á. Navia-Vázquez, and A.R. Figueiras-Vidal Support vector machines framework for linear signal processing Signal Proces. 85 12 2005 2316 2326
-
(2005)
Signal Proces.
, vol.85
, Issue.12
, pp. 2316-2326
-
-
Rojo-Álvarez, J.L.1
Camps-Valls, G.2
Martínez-Ramón, M.3
Soria-Olivas, E.4
Navia-Vázquez Á.5
Figueiras-Vidal, A.R.6
-
14
-
-
34147187067
-
Support vector machines for nonlinear kernel ARMA system identification
-
M. Martínez-Ramón, J.L. Rojo-Álvarez, G. Camps-Valls, J. Muñoz-Marí, Á. Navia-Vázquez, E. Soria-Olivas, and A.R. Figueiras-Vidal Support vector machines for nonlinear kernel ARMA system identification IEEE Trans. Neural Networks 17 2006 1617 1622
-
(2006)
IEEE Trans. Neural Networks
, vol.17
, pp. 1617-1622
-
-
Martínez-Ramón, M.1
Rojo-Álvarez, J.L.2
Camps-Valls, G.3
Muñoz-Marí, J.4
Navia-Vázquez Á.5
Soria-Olivas, E.6
Figueiras-Vidal, A.R.7
-
16
-
-
0032638628
-
Least squares support vector machine classifiers
-
J.A. Suykens, and J. Vandewalle Least squares support vector machine classifiers Neural Proces. Lett. 9 1999 293 300
-
(1999)
Neural Proces. Lett.
, vol.9
, pp. 293-300
-
-
Suykens, J.A.1
Vandewalle, J.2
-
17
-
-
0002709342
-
Feature selection via concave minimization and support vector machines
-
Morgan Kaufman San Francisco, CA
-
P.S. Bradley, and O.L. Mangasarian Feature selection via concave minimization and support vector machines Proc. 15th Intl. Conf. on Machine Learning 1998 Morgan Kaufman San Francisco, CA 82 90
-
(1998)
Proc. 15th Intl. Conf. on Machine Learning
, pp. 82-90
-
-
Bradley, P.S.1
Mangasarian, O.L.2
-
18
-
-
0033681936
-
Support vectors selection by linear programming
-
Como, Italy
-
V. Kecman, I. Hadzic, Support vectors selection by linear programming, in: Proc. Intl. Joint Conf. on Neural Networks, vol. 5, Como, Italy, 2000, pp. 193-198.
-
(2000)
Proc. Intl. Joint Conf. on Neural Networks
, vol.5
, pp. 193-198
-
-
Kecman, V.1
Hadzic, I.2
-
19
-
-
0036887673
-
Linear programming support vector machines
-
W. Zhou, L. Zhang, and L. Jiao Linear programming support vector machines Pattern Recogn. 35 2002 2927 2936
-
(2002)
Pattern Recogn.
, vol.35
, pp. 2927-2936
-
-
Zhou, W.1
Zhang, L.2
Jiao, L.3
-
20
-
-
84899024917
-
1-Norm support vector machines
-
S. Thrun, L. Saul, B. Schölkopf, MIT Press Cambridge, MA
-
J. Zhu, S. Rosset, T. Hastie, and R. Tibshirani 1-Norm support vector machines S. Thrun, L. Saul, B. Schölkopf, Advances in Neural Information Proc. Sys. vol. 16 2004 MIT Press Cambridge, MA 49 56
-
(2004)
Advances in Neural Information Proc. Sys.
, vol.16 VOL.
, pp. 49-56
-
-
Zhu, J.1
Rosset, S.2
Hastie, T.3
Tibshirani, R.4
-
22
-
-
77049107099
-
Designing model based classifiers by emphasizing soft targets
-
S. El Jelali, A. Lyhyaoui, and A.R. Figueiras-Vidal Designing model based classifiers by emphasizing soft targets Fundam. Inf. 96 2009 419 433
-
(2009)
Fundam. Inf.
, vol.96
, pp. 419-433
-
-
El Jelali, S.1
Lyhyaoui, A.2
Figueiras-Vidal, A.R.3
-
23
-
-
0033485370
-
Ensemble learning via negative correlation
-
Y. Liu, and X. Yao Ensemble learning via negative correlation Neural Networks 12 1999 1399 1404
-
(1999)
Neural Networks
, vol.12
, pp. 1399-1404
-
-
Liu, Y.1
Yao, X.2
-
24
-
-
0033280266
-
Simultaneous training of negatively correlated neural networks in an ensemble
-
Y. Liu, and X. Yao Simultaneous training of negatively correlated neural networks in an ensemble IEEE Trans. Syst. Man Cybern., Part B: Cybern. 29 1999 716 725
-
(1999)
IEEE Trans. Syst. Man Cybern., Part B: Cybern.
, vol.29
, pp. 716-725
-
-
Liu, Y.1
Yao, X.2
-
25
-
-
0031211090
-
A decision-theoretic generalization of on-line learning and an application to boosting
-
Y. Freund, and R.E. Schapire A decision-theoretic generalization of on-line learning and an application to boosting J. Comput. Syst. Sci. 55 1997 119 139
-
(1997)
J. Comput. Syst. Sci.
, vol.55
, pp. 119-139
-
-
Freund, Y.1
Schapire, R.E.2
-
26
-
-
0033281701
-
Improved boosting algorithms using confidence-rated predictions
-
R.E. Schapire, and Y. Singer Improved boosting algorithms using confidence-rated predictions Mach. Learn. 37 1999 297 336
-
(1999)
Mach. Learn.
, vol.37
, pp. 297-336
-
-
Schapire, R.E.1
Singer, Y.2
-
29
-
-
0002859310
-
Learning algorithms for classification: A comparison on handwritten digit recognition
-
J.H. Oh, C. Kwon, S. Cho, World Scientific Singapore
-
Y. LeCun, L.D. Jackel, H.A. Eduard, N. Bottou, C. Cortes, J.S. Denker, H. Drucker, E. Sackinger, P. Simard, and V. Vapnik Learning algorithms for classification: a comparison on handwritten digit recognition J.H. Oh, C. Kwon, S. Cho, Neural Networks: The Statistical Mechanics Perspective 1995 World Scientific Singapore 261 276
-
(1995)
Neural Networks: The Statistical Mechanics Perspective
, pp. 261-276
-
-
Lecun, Y.1
Jackel, L.D.2
Eduard, H.A.3
Bottou, N.4
Cortes, C.5
Denker, J.S.6
Drucker, H.7
Sackinger, E.8
Simard, P.9
Vapnik, V.10
-
30
-
-
84956609453
-
Adaboosting neural networks
-
W. Gerstner, A. Germond, M. Hasler, J.D. Nicoud, Springer Berlin
-
H. Schwenk, and Y. Bengio Adaboosting neural networks W. Gerstner, A. Germond, M. Hasler, J.D. Nicoud, Proc. 7th Intl. Conf. on Artificial Neural Networks (LNCS 1327) 1997 Springer Berlin 967 972
-
(1997)
Proc. 7th Intl. Conf. on Artificial Neural Networks (LNCS 1327)
, pp. 967-972
-
-
Schwenk, H.1
Bengio, Y.2
-
31
-
-
0032645080
-
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
-
E. Bauer, and R. Kohavi An empirical comparison of voting classification algorithms: bagging, boosting, and variants Mach. Learn. 36 1999 105 139
-
(1999)
Mach. Learn.
, vol.36
, pp. 105-139
-
-
Bauer, E.1
Kohavi, R.2
-
32
-
-
0034250160
-
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
-
T.G. Dietterich An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization Mach. Learn. 40 2000 139 157
-
(2000)
Mach. Learn.
, vol.40
, pp. 139-157
-
-
Dietterich, T.G.1
-
33
-
-
0000275022
-
Prediction games and arcing algorithms
-
L. Breiman Prediction games and arcing algorithms Neural Comput. 11 1999 1493 1517
-
(1999)
Neural Comput.
, vol.11
, pp. 1493-1517
-
-
Breiman, L.1
-
35
-
-
21844445229
-
Efficient margin maximizing with boosting
-
G. Rätsch, and M.K. Warmuth Efficient margin maximizing with boosting J. Mach. Learn. Res. 6 2005 2131 2152
-
(2005)
J. Mach. Learn. Res.
, vol.6
, pp. 2131-2152
-
-
Rätsch, G.1
Warmuth, M.K.2
-
36
-
-
33845953137
-
Reducing the overfitting of AdaBoost by controlling its data distribution skewness
-
Y. Sun, S. Todorovic, and J. Li Reducing the overfitting of AdaBoost by controlling its data distribution skewness Intl. J. Pattern Recogn. Artif. Intell. 20 2006 1093 1116
-
(2006)
Intl. J. Pattern Recogn. Artif. Intell.
, vol.20
, pp. 1093-1116
-
-
Sun, Y.1
Todorovic, S.2
Li, J.3
-
39
-
-
39049086240
-
An efficient modified boosting method for solving classification problems
-
C.-X. Zhang, J.-S. Zhang, and G.-Y. Zhang An efficient modified boosting method for solving classification problems J. Comput. Appl. Math. 214 2008 381 392
-
(2008)
J. Comput. Appl. Math.
, vol.214
, pp. 381-392
-
-
Zhang, C.-X.1
Zhang, J.-S.2
Zhang, G.-Y.3
-
40
-
-
77950861838
-
Boosting through optimization of margin distributions
-
C. Shen, and H. Li Boosting through optimization of margin distributions IEEE Trans. Neural Networks 21 4 2010 659 666
-
(2010)
IEEE Trans. Neural Networks
, vol.21
, Issue.4
, pp. 659-666
-
-
Shen, C.1
Li, H.2
-
41
-
-
84937643696
-
Neighborhood guided smoothed emphasis for real adaboost ensembles
-
A. Aachad, A. Omari, and A.R. Figueiras-Vidal Neighborhood guided smoothed emphasis for real adaboost ensembles Neural Proc. Lett. 10 2014 1 11
-
(2014)
Neural Proc. Lett.
, vol.10
, pp. 1-11
-
-
Aachad, A.1
Omari, A.2
Figueiras-Vidal, A.R.3
-
42
-
-
84956981949
-
Performance degradation in boosting
-
J. Kittler, F. Roli, Springer Berlin
-
J. Wickramaratna, S. Holden, and B. Buxton Performance degradation in boosting J. Kittler, F. Roli, Multiple Classifier Systems (LNCS 2096) 2001 Springer Berlin 11 21
-
(2001)
Multiple Classifier Systems (LNCS 2096)
, pp. 11-21
-
-
Wickramaratna, J.1
Holden, S.2
Buxton, B.3
-
43
-
-
55749096877
-
Boosting method for local learning in statistical pattern recognition
-
M. Kawakita, and S. Eguchi Boosting method for local learning in statistical pattern recognition Neural Comput. 20 2008 2792 2838
-
(2008)
Neural Comput.
, vol.20
, pp. 2792-2838
-
-
Kawakita, M.1
Eguchi, S.2
-
46
-
-
70350550156
-
An AdaBoost algorithm with SVM based on nonlinear decision function
-
Wuhan, China
-
W. Wu, Z. Yanan, W. Linlin, An AdaBoost algorithm with SVM based on nonlinear decision function, in: Proc. Intl. Conf. on Computational Intell. and Natural Computing, Wuhan, China, 2009, pp. 22-25.
-
(2009)
Proc. Intl. Conf. on Computational Intell. and Natural Computing
, pp. 22-25
-
-
Wu, W.1
Yanan, Z.2
Linlin, W.3
-
47
-
-
70449389296
-
Creating an ensemble of diverse support vector machines using AdaBoost
-
Atlanta, GA, USA
-
N. Lima, A. Neto, J. de Melo, Creating an ensemble of diverse support vector machines using AdaBoost, in: Proc. Intl. Joint Conf. on Neural Networks, Atlanta, GA, USA, 2009, pp. 1802-1806.
-
(2009)
Proc. Intl. Joint Conf. on Neural Networks
, pp. 1802-1806
-
-
Lima, N.1
Neto, A.2
De Melo, J.3
-
48
-
-
77956501257
-
A boosting method based on SVM for relevance feedback in content-based 3D model retrieval
-
Chengdu, China
-
T. Wei, Z. Qin, X. Cao, B. Leng, A boosting method based on SVM for relevance feedback in content-based 3D model retrieval, in: Proc. 2nd Intl. Conf. on Software Engineering and Data Mining, Chengdu, China, 2010, pp. 517-522.
-
(2010)
Proc. 2nd Intl. Conf. on Software Engineering and Data Mining
, pp. 517-522
-
-
Wei, T.1
Qin, Z.2
Cao, X.3
Leng, B.4
-
49
-
-
44649197212
-
AdaBoost with SVM-based component classifiers
-
X. Li, L. Wang, and E. Sung AdaBoost with SVM-based component classifiers Eng. Appl. Artif. Intell. 21 2008 785 795
-
(2008)
Eng. Appl. Artif. Intell.
, vol.21
, pp. 785-795
-
-
Li, X.1
Wang, L.2
Sung, E.3
-
50
-
-
0142025124
-
Constructing support vector machine ensemble
-
H.-C. Kim, S. Pang, H.-M. Je, D. Kim, and S.Y. Bang Constructing support vector machine ensemble Pattern Recogn. 36 2003 2757 2767
-
(2003)
Pattern Recogn.
, vol.36
, pp. 2757-2767
-
-
Kim, H.-C.1
Pang, S.2
Je, H.-M.3
Kim, D.4
Bang, S.Y.5
-
51
-
-
33847331702
-
Boosting of support vector machines with application to editing
-
Los Angeles, CA, USA
-
P. Rangel, F. Lozano, E. García, Boosting of support vector machines with application to editing, in: Proc. 4th Intl. Conf. on Machine Learning and Applications, Los Angeles, CA, USA, 2005, pp. 6.
-
(2005)
Proc. 4th Intl. Conf. on Machine Learning and Applications
, pp. 6
-
-
Rangel, P.1
Lozano, F.2
García, E.3
-
52
-
-
68749085172
-
Real AdaBoost ensembles with emphasized subsampling
-
J. Cabestany, F. Sandoval, A. Prieto, J. Corchado, Springer Berlin
-
S. Muñoz Romero, J. Arenas-García, and V. Gómez-Verdejo Real AdaBoost ensembles with emphasized subsampling J. Cabestany, F. Sandoval, A. Prieto, J. Corchado, Bio-Inspired Systems: Computational and Ambient Intelligence (LNCS 5517) 2009 Springer Berlin 440 447
-
(2009)
Bio-Inspired Systems: Computational and Ambient Intelligence (LNCS 5517)
, pp. 440-447
-
-
Muñoz Romero, S.1
Arenas-García, J.2
Gómez-Verdejo, V.3
-
53
-
-
84861596906
-
Bootstrapping boosted random ferns for discriminative and efficient object classification
-
M. Villamizar, J. Andrade-Cetto, A. Sanfeliu, and F. Moreno-Noguer Bootstrapping boosted random ferns for discriminative and efficient object classification Pattern Recogn. 45 2012 3141 3153
-
(2012)
Pattern Recogn.
, vol.45
, pp. 3141-3153
-
-
Villamizar, M.1
Andrade-Cetto, J.2
Sanfeliu, A.3
Moreno-Noguer, F.4
-
54
-
-
2142775432
-
Multicategory support vector machines. Theory and application to the classification of microarray data and satellite radiance data
-
Y. Lee, Y. Lin, and G. Wahba Multicategory support vector machines. Theory and application to the classification of microarray data and satellite radiance data J. Am. Stat. Assoc. 99 2004 67 81
-
(2004)
J. Am. Stat. Assoc.
, vol.99
, pp. 67-81
-
-
Lee, Y.1
Lin, Y.2
Wahba, G.3
-
55
-
-
84870238942
-
Multitask multiclass support vector machines: Model and experiments
-
Y. Ji, and S. Sun Multitask multiclass support vector machines: model and experiments Pattern Recogn. 46 3 2013 914 924
-
(2013)
Pattern Recogn.
, vol.46
, Issue.3
, pp. 914-924
-
-
Ji, Y.1
Sun, S.2
-
59
-
-
84898409192
-
Weighted sampling for large-scale boosting
-
M. Everingham, C.J. Needham, R. Fraile, British Machine Vision Assoc. Leeds, UK
-
Z. Kalal, J. Matas, and K. Mikolajczyk Weighted sampling for large-scale boosting M. Everingham, C.J. Needham, R. Fraile, Proc. of the British Machine Vision Conference 2008 British Machine Vision Assoc. Leeds, UK 42.1 42.10
-
(2008)
Proc. of the British Machine Vision Conference
, pp. 421-4210
-
-
Kalal, Z.1
Matas, J.2
Mikolajczyk, K.3
-
60
-
-
78649934709
-
-
School of Information and Computer Sciences, University of California Irvine < >
-
A. Frank, and A. Asuncion UCI Machine Learning Repository 2010 School of Information and Computer Sciences, University of California Irvine < http://archive.ics.uci.edu/ml >
-
(2010)
UCI Machine Learning Repository
-
-
Frank, A.1
Asuncion, A.2
-
61
-
-
0032594960
-
Moderating the outputs of support vector machine classifiers
-
J.Y. Kwok Moderating the outputs of support vector machine classifiers IEEE Trans. Neural Networks 10 1999 1018 1031
-
(1999)
IEEE Trans. Neural Networks
, vol.10
, pp. 1018-1031
-
-
Kwok, J.Y.1
-
62
-
-
0000696616
-
Neural networks and related methods for classification
-
B.D. Ripley Neural networks and related methods for classification J. Roy. Stat. Soc. 56 1994 409 456
-
(1994)
J. Roy. Stat. Soc.
, vol.56
, pp. 409-456
-
-
Ripley, B.D.1
|