-
3
-
-
0036161011
-
Choosing multiple parameters for support vector machines
-
DOI 10.1023/A:1012450327387
-
O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee, Choosing multiple parameters for support vector machines, Machine Learning 46(1/3) (2002) 131-159. (Pubitemid 34129966)
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 131-159
-
-
Chapelle, O.1
Vapnik, V.2
Bousquet, O.3
Mukherjee, S.4
-
4
-
-
8844278523
-
Learning the kernel matrix with semidefinite programming
-
G. R. G. Lanckriet, N. Cristianini, P. Bartlett, L. E. Ghaoui, and M. I. Jordan, Learning the kernel matrix with semidefinite programming, Journal of Machine Learning Research 5 (2004) 27-72.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 27-72
-
-
Lanckriet, G.R.G.1
Cristianini, N.2
Bartlett, P.3
Ghaoui, L.E.4
Jordan, M.I.5
-
7
-
-
72749092885
-
-
H. W. Mewes, D. Frishman, C. Gruber, B. Geier, D. Haase, A. Kaps, K. Lemcke, G. Mannhaupt, F. Pfeiffer, C. Schüller, S. Stocker, and B. Weil, MIPS: A database for genomes and protein sequences (2002).
-
(2002)
MIPS: A Database for Genomes and Protein Sequences
-
-
Mewes, H.W.1
Frishman, D.2
Gruber, C.3
Geier, B.4
Haase, D.5
Kaps, A.6
Lemcke, K.7
Mannhaupt, G.8
Pfeiffer, F.9
Schüller, C.10
Stocker, S.11
Weil, B.12
-
8
-
-
0041965869
-
Text classification using string kernels
-
H. Lodhi, C. Saunders, J. Shawe-Taylor, N. Cristianini, and C. Watkins, Text classification using string kernels, Journal of Machine Learning Research 2 (2002) 419-444.
-
(2002)
Journal of Machine Learning Research
, vol.2
, pp. 419-444
-
-
Lodhi, H.1
Saunders, C.2
Shawe-Taylor, J.3
Cristianini, N.4
Watkins, C.5
-
9
-
-
33646008572
-
Appropriate kernel functions for support vector machine learning with sequences of symbolic data
-
J. Winkler, M. Niranjan, and N. D. Lawrence (Eds.),(Springer), Deterministic and Statistical Methods in Machine Learning
-
B. Vanschoenwinkel, B. Manderick, Appropriate kernel functions for support vector machine learning with sequences of symbolic data, in: J. Winkler, M. Niranjan, and N. D. Lawrence (Eds.), Deterministic and Statistical Methods in Machine Learning, Vol.3635 of LNCS (Springer, 2004), pp. 256-280.
-
(2004)
LNCS
, vol.3635
, pp. 256-280
-
-
Vanschoenwinkel, B.1
Manderick, B.2
-
10
-
-
33745776113
-
Large scale multiple kernel learning
-
S. Sonnenburg, G. Rtsch, C. Schafer, and B. Scholkopf, Large scale multiple kernel learning, Journal of Machine Learning Research 7 (2006) 1531-1565.
-
(2006)
Journal of Machine Learning Research
, vol.7
, pp. 1531-1565
-
-
Sonnenburg, S.1
Rtsch, G.2
Schafer, C.3
Scholkopf, B.4
-
11
-
-
14344252374
-
Multiple kernel learning, conic duality, and the SMO algorithm
-
ed. C. E. Brodley (ACM)
-
F. R. Bach, G. R. G. Lanckriet, and M. I. Jordan, Multiple kernel learning, conic duality, and the SMO algorithm, in ICML, ed. C. E. Brodley (ACM, 2004), pp. 41- 48.
-
(2004)
ICML
, pp. 41-48
-
-
Bach, F.R.1
Lanckriet, G.R.G.2
Jordan, M.I.3
-
12
-
-
34547971778
-
More efficiency in multiple kernel learning
-
Accepted
-
A. Rakotomamonjy, F. R. Bach, S. Canu, and Y. Grandvalet, More efficiency in multiple kernel learning, in Proceedings of the Twenty-fourth International Conference on Machine Learning (ICML), 2007, accepted.
-
(2007)
Proceedings of the Twenty-fourth International Conference on Machine Learning (ICML)
-
-
Rakotomamonjy, A.1
Bach, F.R.2
Canu, S.3
Grandvalet, Y.4
-
13
-
-
38049072277
-
Improving svm performance using a linear combination of kernels
-
of LNCS (Springer)
-
L. Diosan, M. Oltean, A. Rogozan, and J. P. Pecuchet, Improving svm performance using a linear combination of kernels, in Adaptive and Natural Computing Algorithms, ICANNGA'07, Vol.4432 of LNCS (Springer, 2007), pp. 218-227.
-
(2007)
Adaptive and Natural Computing Algorithms, ICANNGA'07
, vol.4432
, pp. 218-227
-
-
Diosan, L.1
Oltean, M.2
Rogozan, A.3
Pecuchet, J.P.4
-
14
-
-
35048816088
-
Combined kernel function for support vector machine and learning method based on evolutionary algorithm
-
N. R. Pal, N. Kasabov, R. K. Mudi, S. Pal, and S. K. Parui (Eds.), of LNCS (Springer, 2004
-
H.-N. Nguyen, S.-Y. Ohn, and W.-J. Choi, Combined kernel function for support vector machine and learning method based on evolutionary algorithm, in: N. R. Pal, N. Kasabov, R. K. Mudi, S. Pal, and S. K. Parui (Eds.), Neural Information Pro- cessing, 11th International Conference, ICONIP 2004, Vol.3316 of LNCS (Springer, 2004), pp. 1273-1278.
-
(2004)
Neural Information Pro- Cessing, 11th International Conference, ICONIP
, vol.3316
, pp. 1273-1278
-
-
Nguyen, H.-N.1
Ohn, S.-Y.2
Choi, W.-J.3
-
15
-
-
35048874390
-
Evolutionary parameter estimation algorithm for combined kernel function in support vector machine
-
C.-H. Chi and K.-Y. Lam (Eds.), of LNCS (Springer, 2004
-
S.-Y. Ohn, H.-N. Nguyen, and S.-D. Chi, Evolutionary parameter estimation algorithm for combined kernel function in support vector machine, in: C.-H. Chi and K.-Y. Lam (Eds.), Content Computing, Advanced Workshop on Content Computing, AWCC 2004, Vol.3309 of LNCS (Springer, 2004), pp. 481-486.
-
(2004)
Content Computing, Advanced Workshop on Content Computing, AWCC 2004
, vol.3309
, pp. 481-486
-
-
Ohn, S.-Y.1
Nguyen, H.-N.2
Chi, S.-D.3
-
16
-
-
24944435114
-
Determining optimal decision model for support vector machine by genetic algorithm
-
J. Zhang, J.-H. He, and Y. Fu (Eds.), Computational and Information Science, First International Sympo- sium, CIS 2004, (Springer)
-
S.-Y. Ohn, H.-N. Nguyen, D. S. Kim, and J. S. Park, Determining optimal decision model for support vector machine by genetic algorithm, in: J. Zhang, J.-H. He, and Y. Fu (Eds.), Computational and Information Science, First International Sympo- sium, CIS 2004, Vol.3314 of LNCS (Springer, 2004), pp. 895-902.
-
(2004)
LNCS
, vol.3314
, pp. 895-902
-
-
Ohn, S.-Y.1
Nguyen, H.-N.2
Kim, D.S.3
Park, J.S.4
-
17
-
-
47249105274
-
Genetically constructed kernels for support vector machines
-
Springer
-
R. S. S. Lessmann and S. Crone, Genetically constructed kernels for support vector machines, in Proc. of German Operations Research (Springer, 2005), pp. 257-262.
-
(2005)
Proc. of German Operations Research
, pp. 257-262
-
-
Lessmann, R.S.S.1
Crone, S.2
-
19
-
-
84898936871
-
On kernel-target alignment
-
T. G. Dietterich S. Becker and Z. Ghahramani (Eds.), December 3-8, 2001, Vancouver, British Columbia, Canada] (MIT Press
-
N. Cristianini, J. Shawe-Taylor, A. Elisseeff, and J. S. Kandola, On kernel-target alignment, in: T. G. Dietterich, S. Becker, and Z. Ghahramani (Eds.), Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada] (MIT Press, 2001), pp. 367-373.
-
(2001)
Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic NIPS, 2001
, pp. 367-373
-
-
Cristianini, N.1
Shawe-Taylor, J.2
Elisseeff, A.3
Kandola, J.S.4
-
23
-
-
0002714543
-
Making large-scale SVM learning practical, in Advances
-
eds. B. Scholkopf, C. J. C. Burges, and A. J. Smola (MIT Press)
-
T. Joachims, Making large-scale SVM learning practical, in Advances in Kernel Method - Support Vector Learning, eds. B. Scholkopf, C. J. C. Burges, and A. J. Smola (MIT Press, 1999), pp. 169-184.
-
(1999)
Kernel Method - Support Vector Learning
, pp. 169-184
-
-
Joachims, T.1
-
24
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
Kluwer Academic
-
J. C. Burges, A tutorial on support vector machines for pattern recognition, in Knowl- edge Discovery and Data Mining, Vol.2 (Kluwer Academic, 1998), pp. 121-167.
-
(1998)
Knowl- Edge Discovery and Data Mining
, vol.2
, pp. 121-167
-
-
Burges, J.C.1
-
26
-
-
0000874557
-
Theoretical foundations of the potential function method in pattern recognition learning
-
M. A. Aizerman, E. M. Braverman, and L. I. Rozonóer, Theoretical foundations of the potential function method in pattern recognition learning, Automation and Remote Control 25 (1964) 821-837.
-
(1964)
Automation and Remote Control
, vol.25
, pp. 821-837
-
-
Aizerman, M.A.1
Braverman, E.M.2
Rozonóer, L.I.3
-
27
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
B. E. Boser, I. Guyon, and V. Vapnik, A training algorithm for optimal margin classifiers, in COLT, 1992, pp. 144-152.
-
(1992)
COLT
, pp. 144-152
-
-
Boser, B.E.1
Guyon, I.2
Vapnik, V.3
-
28
-
-
0346451740
-
-
T. K. Leen, T. G. Dietterich, and V. Tresp (Eds.) NIPS (MIT Press
-
B. Schölkopf, The kernel trick for distances in T. K. Leen, T. G. Dietterich, and V. Tresp (Eds.) NIPS (MIT Press, 2000), pp. 301-307.
-
(2000)
The Kernel Trick for Distances
, pp. 301-307
-
-
Schölkopf, B.1
-
29
-
-
34249753618
-
Support-vector networks
-
C. Cortes and V. Vapnik, Support-vector networks, Machine Learning 20 (1995) 273-297.
-
(1995)
Machine Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
31
-
-
29144521785
-
The genetic kernel support vector machine: Description and evaluation
-
T. Howley and M. G. Madden, The genetic kernel support vector machine: Description and evaluation, Artif. Intell. Rev. 24(3-4) (2005) 379-395.
-
(2005)
Artif. Intell. Rev.
, vol.24
, Issue.3-4
, pp. 379-395
-
-
Howley, T.1
Madden, M.G.2
-
32
-
-
33749836050
-
An evolutionary approach to automatic kernel construction
-
S. D. Kollias, A. Stafylopatis, W. Duch, and E. Oja (Eds.), Artificial Neural Networks - ICANN, 2006, Springer
-
T. Howley and M. G. Madden, An evolutionary approach to automatic kernel construction, in: S. D. Kollias, A. Stafylopatis, W. Duch, and E. Oja (Eds.), Artificial Neural Networks - ICANN 2006, Vol.4132 of LNCS (Springer, 2006), pp. 417-426.
-
(2006)
LNCS
, vol.4132
, pp. 417-426
-
-
Howley, T.1
Madden, M.G.2
-
33
-
-
47349110721
-
Evolving kernel functions for svms by genetic programming
-
Ohio, USA, Accepted
-
L. Dio̧san, A. Rogozan, J.-P. Pcuchet, Evolving kernel functions for svms by genetic programming, in The 2007 International Conference on Machine Learning and Ap- plications (ICMLA'07 ), Ohio, USA, 2007, accepted.
-
(2007)
The 2007 International Conference on Machine Learning and Ap- Plications (ICMLA'07 )
-
-
Dio̧san, L.1
Rogozan, A.2
Pcuchet, J.-P.3
-
34
-
-
33750228090
-
Genetic programming for kernel-based learning with co-evolving subsets selection
-
T. P. Runarsson, H.-G. Beyer, E. K. Burke, J. J. M. Guervos, L. D.Whitley, and X. Yao (Eds.), Parallel Prob- lem Solving from Nature - PPSN IX, (9th PPSN'06), Springer
-
C. Gagne, M. Schoenauer, M. Sebag, and M. Tomassini, Genetic programming for kernel-based learning with co-evolving subsets selection, in: T. P. Runarsson, H.-G. Beyer, E. K. Burke, J. J. M. Guervos, L. D.Whitley, and X. Yao (Eds.), Parallel Prob- lem Solving from Nature - PPSN IX, (9th PPSN'06), Vol.4193 of LNCS (Springer, 2006), pp. 1008-1017.
-
(2006)
LNCS
, vol.4193
, pp. 1008-1017
-
-
Gagne, C.1
Schoenauer, M.2
Sebag, M.3
Tomassini, M.4
-
38
-
-
14344252374
-
-
ACM, 2004
-
F. R. Bach, G. R. G. Lanckriet, and M. I. Jordan, Multiple kernel learning, conic duality, and the SMO algorithm, in Machine Learning, Proceedings of ICML 2004 (ACM, 2004), p. 6.
-
(2004)
Multiple Kernel Learning Conic Duality and the SMO Algorithm in Machine Learning Proceedings of ICML
, pp. 6
-
-
Bach, F.R.1
Lanckriet, G.R.G.2
Jordan, M.I.3
-
39
-
-
31844435594
-
Hierarchic bayesian models for kernel learning
-
M. Girolami and S. Rogers, Hierarchic bayesian models for kernel learning, in ICML, 2005, pp. 241-248.
-
(2005)
ICML
, pp. 241-248
-
-
Girolami, M.1
Rogers, S.2
-
40
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
B. Schölkopf, C. J. C. Burges, A. J. Smola (Eds.), (MIT Press
-
J. Platt, Fast training of support vector machines using sequential minimal optimization, in: B. Schölkopf, C. J. C. Burges, A. J. Smola (Eds.), Advances in Kernel Methods - Support Vector Learning (MIT Press, 1999), pp. 185-208.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 185-208
-
-
Platt, J.1
-
42
-
-
0002881568
-
Uniform crossover in genetic algorithms
-
G. Syswerda, Uniform crossover in genetic algorithms, in ICGA, 1989, pp. 2-9.
-
(1989)
ICGA
, pp. 2-9
-
-
Syswerda, G.1
-
43
-
-
0001842954
-
A study of reproduction in generational and steady state genetic algorithms
-
G. J. E. Rawlins (Ed.)
-
G. Syswerda, A study of reproduction in generational and steady state genetic algorithms, in: G. J. E. Rawlins (Ed.), Proceedings of FOGA Conference (Morgan Kaufmann, 1991), pp. 94-101.
-
(1991)
Proceedings of FOGA Conference (Morgan Kaufmann)
, pp. 94-101
-
-
Syswerda, G.1
-
47
-
-
0022559425
-
Optimization of control parameters for genetic algorithms
-
J. J. Grefenstette, Optimization of control parameters for genetic algorithms, IEEE Transactions on Systems, Man, and Cybernetics SMC 16(1) (1986) 122-128.
-
(1986)
IEEE Transactions on Systems, Man, and Cybernetics SMC
, vol.16
, Issue.1
, pp. 122-128
-
-
Grefenstette, J.J.1
-
48
-
-
85027514443
-
Parallel optimization of evolutionary algorithms
-
Y. Davidor, H.-P. Schwefel (Eds.), Lecture Notes in Computer Science (Springer Verlag
-
T. Bäck, Parallel optimization of evolutionary algorithms, in: Y. Davidor, H.-P. Schwefel (Eds.), Parallel Problem Solving From Nature - PPSN III, Vol.866 of Lecture Notes in Computer Science (Springer Verlag, 1994), pp. 418-427.
-
(1994)
Parallel Problem Solving from Nature - PPSN III
, vol.866
, pp. 418-427
-
-
Bäck, T.1
-
49
-
-
84958987754
-
The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets
-
W. Banzhaf, F. D. Francone, and P. Nordin, The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets, Lecture Notes in Computer Science 1141 (1996) 300-309.
-
(1996)
Lecture Notes in Computer Science
, vol.1141
, pp. 300-309
-
-
Banzhaf, W.1
Francone, F.D.2
Nordin, P.3
-
50
-
-
0041312683
-
Genetic programming with one-point crossover
-
P. K. Chawdhry, R. Roy, R. K. Pant (Eds.), Springer-Verlag, London
-
R. Poli and W. B. Langdon, Genetic programming with one-point crossover, in: P. K. Chawdhry, R. Roy, R. K. Pant (Eds.), Soft Computing in Engineering Design and Manufacturing (Springer-Verlag, London, 1997), pp. 180-189.
-
(1997)
Soft Computing in Engineering Design and Manufacturing
, pp. 180-189
-
-
Poli, R.1
Langdon, W.B.2
-
51
-
-
33746061251
-
Genetic programming: Analysis of optimal mutation rates in a problem with varying difficulty
-
G. C. J. Sutcliffe, R. G. Goebel (Eds.)
-
A. Piszcz and T. Soule, Genetic programming: Analysis of optimal mutation rates in a problem with varying difficulty, in: G. C. J. Sutcliffe, R. G. Goebel (Eds.), Proceed- ings of the Nineteenth International Florida Artificial Intelligence Research Society Conference (American Association for Artificial Intelligence, 2006), pp. 451-456.
-
(2006)
Proceed- Ings of the Nineteenth International Florida Artificial Intelligence Research Society Conference (American Association for Artificial Intelligence
, pp. 451-456
-
-
Piszcz, A.1
Soule, T.2
-
52
-
-
34547980120
-
A kernel path algorithm for support vector machines
-
ACM Press
-
G. Wang, D.-Y. Yeung, and F. H. Lochovsky, A kernel path algorithm for support vector machines, in ICML '07: Proceedings of the 24th International Conference on Machine Learning (ACM Press, 2007), pp. 951-958.
-
(2007)
ICML '07: Proceedings of the 24th International Conference on Machine Learning
, pp. 951-958
-
-
Wang, G.1
Yeung, D.-Y.2
Lochovsky, F.H.3
-
53
-
-
77958130084
-
Machines noyaux pour lapprentissage statistique
-
M. R. Hestenes and E. Stiefel, Machines noyaux pour lapprentissage statistique, Technologies de l'information 4(1) (2007) 1-20.
-
(2007)
Technologies de l'Information
, vol.4
, Issue.1
, pp. 1-20
-
-
Hestenes, M.R.1
Stiefel, E.2
-
55
-
-
0004196396
-
An investigation into the sensitivity of genetic programming to the frequency of leaf selection during subtree crossover
-
J. R. Koza, D. E. Goldberg, D. B. Fogel, R. L. Riolo (Eds.), (MIT Press)
-
P. J. Angeline, An investigation into the sensitivity of genetic programming to the frequency of leaf selection during subtree crossover, in: J. R. Koza, D. E. Goldberg, D. B. Fogel, R. L. Riolo (Eds.), Genetic Programming 1996: Proceedings of the First Annual Conference (MIT Press, 1996), pp. 21-29.
-
(1996)
Genetic Programming 1996: Proceedings of the First Annual Conference
, pp. 21-29
-
-
Angeline, P.J.1
-
57
-
-
0026274677
-
Meta-evolutionary programming
-
R. R. Chen (Ed.), Maple
-
D. B. Fogel, L. J. Fogel, and J. W. Atmar, Meta-evolutionary programming, in: R. R. Chen (Ed.), Proc. of the 25th Asilomar Conf. on Signals, Systems, and Computers (Maple, 1991), pp. 540-545.
-
(1991)
Proc. of the 25th Asilomar Conf. on Signals, Systems, and Computers
, pp. 540-545
-
-
Fogel, D.B.1
Fogel, L.J.2
Atmar, J.W.3
-
58
-
-
0032203257
-
Gradient-based learning applied to document recognition
-
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE 86(11) (1998) 2278-2324.
-
(1998)
Proceedings of the IEEE
, vol.86
, Issue.11
, pp. 2278-2324
-
-
Lecun, Y.1
Bottou, L.2
Bengio, Y.3
Haffner, P.4
-
59
-
-
0003250435
-
Single-layer learning revisited: A stepwise procedure for building and training a neural network
-
S. Knerr, L. Personnaz, and G. Dreyfus, Single-layer learning revisited: A stepwise procedure for building and training a neural network, Neurocomputing: Algorithms, Architectures and Applications F68 (1990) 41-50.
-
(1990)
Neurocomputing: Algorithms, Architectures and Applications F68
, pp. 41-50
-
-
Knerr, S.1
Personnaz, L.2
Dreyfus, G.3
|