-
2
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
D. Haussler (Ed.), Pittsburgh: ACM Press
-
Boser BE, Guyon IM, Vapnik VN (1992) A training algorithm for optimal margin classifiers. In: Haussler D (ed) 5th annual ACM workshop on COLT. ACM Press, Pittsburgh, pp 144-152.
-
(1992)
5th Annual ACM Workshop on COLT
, pp. 144-152
-
-
Boser, B.E.1
Guyon, I.M.2
Vapnik, V.N.3
-
6
-
-
0036772522
-
Bayesian automatic relevance determination algorithms for classifying gene expression data
-
Li Y, Campbell C, Tipping M (2002) Bayesian automatic relevance determination algorithms for classifying gene expression data. Bioinformatics 18(10): 1332-1339.
-
(2002)
Bioinformatics
, vol.18
, Issue.10
, pp. 1332-1339
-
-
Li, Y.1
Campbell, C.2
Tipping, M.3
-
7
-
-
0003748256
-
-
PhD thesis, Dep of Comput and Neural Syst. Calif Inst of Technol, Pasadena, CA
-
MacKay DJ (1992) Bayesian methods for adaptive models. PhD thesis, Dep of Comput and Neural Syst. Calif Inst of Technol, Pasadena, CA.
-
(1992)
Bayesian methods for adaptive models
-
-
MacKay, D.J.1
-
8
-
-
0011944975
-
-
MathWork, Inc, The MathWorks, Inc: Natick
-
MathWork, Inc. (1999) Matlab user's manual, Version 5. 3. Natick, The MathWorks, Inc.
-
(1999)
Matlab User's Manual, Version 5.3
-
-
-
9
-
-
0031375732
-
Nonlinear prediction of chaotic time series using support vector machine
-
New York: Institute of Electrical and Electronics Engineers
-
Mukherjee S, Osuna E, Girosi F (1997) Nonlinear prediction of chaotic time series using support vector machine. In: Proc IEEE workshop on neural networks for signal processing, vol 7. Institute of Electrical and Electronics Engineers, New York, pp 511-519.
-
(1997)
Proc IEEE Workshop on Neural Networks for Signal Processing
, vol.7
, pp. 511-519
-
-
Mukherjee, S.1
Osuna, E.2
Girosi, F.3
-
10
-
-
84956628443
-
Predicting time series with support vector machines
-
Berlin: Springer
-
Muller KR, Smola A, Ratsch G, Scholkopf B, Kohlmorgen J, Vapnik V (1997) Predicting time series with support vector machines. In: Proc int conf on artificial neural networks. Springer, Berlin, p 999.
-
(1997)
Proc Int Conf on Artificial Neural Networks
, pp. 999
-
-
Muller, K.R.1
Smola, A.2
Ratsch, G.3
Scholkopf, B.4
Kohlmorgen, J.5
Vapnik, V.6
-
14
-
-
84899032239
-
The relevance vector machine
-
Tipping M (2000) The relevance vector machine. Adv Neural Inf Process Syst 12: 652-658.
-
(2000)
Adv Neural Inf Process Syst
, vol.12
, pp. 652-658
-
-
Tipping, M.1
-
15
-
-
0001224048
-
Sparse Bayesian learning and the relevance vector machine
-
Tipping ME (2001) Sparse Bayesian learning and the relevance vector machine. J Mach Learn 1: 211-244.
-
(2001)
J Mach Learn
, vol.1
, pp. 211-244
-
-
Tipping, M.E.1
-
18
-
-
84887252594
-
Support method for function approximation regression estimation and signal processing
-
M. Mozer and T. Petsch (Eds.), Cambridge: MIT Press
-
Vapnik V, Golowich S, Smola A (1997) Support method for function approximation regression estimation and signal processing. In: Mozer M, Petsch T (eds) Advance in neural information processing system, vol 9. MIT Press, Cambridge.
-
(1997)
Advance in Neural Information Processing System
, vol.9
-
-
Vapnik, V.1
Golowich, S.2
Smola, A.3
-
19
-
-
0000608177
-
A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline-smoothing problem
-
Wahba G (1985) A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline-smoothing problem. Ann Stat 4: 1378-1402.
-
(1985)
Ann Stat
, vol.4
, pp. 1378-1402
-
-
Wahba, G.1
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