Citation Relationships

Legends: Link to a Model Reference cited by multiple papers


Vapnik V (1995) The Nature of Statistical Learning Theory

References and models cited by this paper

References and models that cite this paper

Aires F, Prigent C, Rossow WB (2004) Neural network uncertainty assessment using Bayesian statistics: a remote sensing application. Neural Comput 16:2415-58 [Journal] [PubMed]
Baram Y (2005) Learning by Kernel Polarization Neural Comput 17:1264-1275
Bo L, Wang L, Jiao L (2006) Feature scaling for kernel fisher discriminant analysis using leave-one-out cross validation. Neural Comput 18:961-78 [Journal] [PubMed]
Chu W, Keerthi SS (2007) Support vector ordinal regression. Neural Comput 19:792-815 [Journal] [PubMed]
Eisenthal Y, Dror G, Ruppin E (2005) Facial Attractiveness: Beauty and the Machine Neural Comput 18:119-142
Fushiki T, Horiuchi S, Tsuchiya T (2006) A maximum likelihood approach to density estimation with semidefinite programming. Neural Comput 18:2777-812 [Journal] [PubMed]
Gunter L, Zhu J (2007) Efficient computation and model selection for the support vector regression. Neural Comput 19:1633-55 [Journal] [PubMed]
Horcholle-Bossavit G, Quenet B, Foucart O (2007) Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system. Biosystems 89:244-56 [Journal] [PubMed]
   Oscillation and coding in a proposed NN model of insect olfaction (Horcholle-Bossavit et al. 2007) [Model]
Ikeda K (2004) An asymptotic statistical theory of polynomial kernel methods Neural Comput 16:1705-1719
Ikeda K, Murata N (2005) Geometrical properties of nu support vector machines with different norms. Neural Comput 17:2508-29 [Journal] [PubMed]
Kurková V (2008) Minimization of error functionals over perceptron networks. Neural Comput 20:252-70 [Journal] [PubMed]
Lin TC, Yu PT (2004) Adaptive two-pass median filter based on support vector machines for image restoration. Neural Comput 16:332-53 [Journal] [PubMed]
Liu X, Hall LO, Bowyer KW (2004) Comments on "a parallel mixture of SVMs for very large scale problems". Neural Comput 16:1345-51 [Journal] [PubMed]
Murata N, Takenouchi T, Kanamori T, Eguchi S (2004) Information geometry of U-Boost and Bregman divergence. Neural Comput 16:1437-81 [Journal] [PubMed]
Park H, Murata N, Amari S (2004) Improving generalization performance of natural gradient learning using optimized regularization by NIC. Neural Comput 16:355-82 [Journal] [PubMed]
Rosasco L, De Vito E, Caponnetto A, Piana M, Verri A (2004) Are loss functions all the same? Neural Comput 16:1063-76 [Journal] [PubMed]
Schmidhuber J, Wierstra D, Gagliolo M, Gomez F (2007) Training recurrent networks by Evolino. Neural Comput 19:757-79 [Journal] [PubMed]
Shpigelman L, Singer Y, Paz R, Vaadia E (2005) Spikernels: predicting arm movements by embedding population spike rate patterns in inner-product spaces. Neural Comput 17:671-90 [Journal] [PubMed]
Shrestha DL, Solomatine DP (2006) Experiments with AdaBoost.RT, an improved boosting scheme for regression. Neural Comput 18:1678-710 [Journal] [PubMed]
Sugiyama M, Kawanabe M, Müller KR (2004) Trading variance reduction with unbiasedness: the regularized subspace information criterion for robust model selection in kernel regression. Neural Comput 16:1077-104 [Journal] [PubMed]
Van Hulle MM (2005) Edgeworth approximation of multivariate differential entropy. Neural Comput 17:1903-10 [PubMed]
Van Hulle MM (2005) Maximum likelihood topographic map formation. Neural Comput 17:503-13 [Journal] [PubMed]
Viéville T, Crahay S (2004) Using an Hebbian learning rule for multi-class SVM classifiers. J Comput Neurosci 17:271-87 [Journal] [PubMed]
Zheng W (2006) Class-incremental generalized discriminant analysis. Neural Comput 18:979-1006 [Journal] [PubMed]
Zheng W, Zhao L, Zou C (2004) A modified algorithm for generalized discriminant analysis. Neural Comput 16:1283-97 [Journal] [PubMed]
(25 refs)