Citation Relationships

Legends: Link to a Model Reference cited by multiple papers

Tsuda K, Akaho S, Kawanabe M, Müller KR (2004) Asymptotic properties of the Fisher kernel. Neural Comput 16:115-37 [PubMed]

References and models cited by this paper

References and models that cite this paper

Albert A (1972) Regression and the Moore-Penrose pseudoinverse
Amari S, Murata N (1993) Statistical theory of learning curves under entropic loss criterion Neural Comput 5:140-154
Amari S, Nagaoka H (2001) Methods of information geometry
Barndorff-nielsen O, Cox D (1989) Asymptotic techniques for use in statistics
Baum E, Haussler D (1989) What size net gives valid generalization Neural Comput 1:151-160
Campbell S, Meyer C (1979) Generalized inverse of linear transformations
Cox D, Hinkley D (1974) Theoretical statistics
Cristianini N, Shawe-taylor J (2000) An introduction to support vector machines
Devroye L, Gyorfi L, Lugosi G (1996) A probabilistic theory of pattern recognition
Eguchi S, Copas J (2001) Information geometry on discriminant analysis and recent development J Korean Stat Soc 27:101-117
Gelfand I, Fomin S (1963) Calculus of variations
Gotoh O (1982) An improved algorithm for matching biological sequences. J Mol Biol 162:705-8 [PubMed]
Haussler D, Kearns M, Seung H, Tishby N (1996) Rigorous learning curve bounds from statistical mechanics Mach Learn 25:195-236
Jaakkola T, Haussler D (1999) Exploiting generative models in discriminative classifiers Advances in neural information processing systems, Kearns M:Solla S:Cohn D, ed. pp.487
Jaakkola T, Meila M, Jebara T (1999) Maximum entropy discrimination Tech. Rep. No. AITR-1668
Kawanabe M, Amari S (1994) Estimation of network parameters in semiparametric stochastic perceptron Neural Comput 6:1244-1261
Malzahn D, Opper M (2002) A variational approach to learning curves Advances in neural information processing systems, Dietterich TG:Becker S:Ghahramani Z, ed. pp.463
Müller KR, Finke M, Murata N, Schulten K, Amari S (1996) A numerical study on learning curves in stochastic multilayer feedforward networks. Neural Comput 8:1085-106 [PubMed]
Müller KR, Mika S, Rätsch G, Tsuda K, Schölkopf B (2001) An introduction to kernel-based learning algorithms. IEEE Trans Neural Netw 12:181-201 [Journal] [PubMed]
Scholkopf B, Smola AJ (2001) Learning with kernels: Support vector machines, regularization, optimization, and beyond
Seeger M (2000) Learning with labeled and unlabeled data Tech Rep
Seeger M (2002) Covariance kernels from Bayesian generative models Advances in neural information processing systems, Dietterich TG:Becker S:Ghahramani Z, ed. pp.905
Seung HS, Sompolinsky H, Tishby N (1992) Statistical mechanics of learning from examples. Phys Rev A 45:6056-6091 [PubMed]
Smith N, Gales M (2002) Speech recognition using SVMs Advances in neural information processing systems, Dietterich TG:Becker S:Ghahramani Z, ed. pp.1197
Sonnenburg S, Ratsch G, Jagota A, Muller KR (2002) New methods for splice site recognition Artificial neural networks--ICANN 2002, Dorronsoro J, ed. pp.329
Sugiyama M (2001) A theory of model selection and active learning for supervised learning Unpublished doctoral dissertation
Tsuda K, Kawanabe M (2002) The leave-one-out kernel Artificial neural networks--ICANN 2002, Dorronsoro J, ed. pp.727
Tsuda K, Kawanabe M, Muller KR (2004) Clustering with the Fisher score Advances in neural information processing systems, Becker S:Thrun S:Obermayer K, ed.
Tsuda K, Kawanabe M, Rätsch G, Sonnenburg S, Müller KR (2002) A new discriminative kernel from probabilistic models. Neural Comput 14:2397-414 [Journal] [PubMed]
van_derVaart A (1998) Asymptotic statistics
Vapnik V (1998) Statistical Learning Theory
Vinokourov A, Girolami M (2002) A probabilistic framework for the hierarchic organization and classification of document collections J Intell Inform Systems 18:153-172
Watanabe S (2001) Algebraic analysis for nonidentifiable learning machines. Neural Comput 13:899-933 [PubMed]
Watkin T, Rau A, Biehl M (1993) The statistical mechanics of learning a rule Rev Mod Phys 65:499
Zhang T, Oles F (2000) The value of unlabeled data for classification problems Proceedings of the Seventeenth International Conference on Machine Learning, Langley P, ed. pp.1191
Zien A, Rätsch G, Mika S, Schölkopf B, Lengauer T, Müller KR (2000) Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics 16:799-807 [PubMed]
(36 refs)