A New Discriminative Kernel from Probabilistic Models

DOI10.1162/08997660260293274zbMath1011.62068OpenAlexW2106868411WikidataQ52029901 ScholiaQ52029901MaRDI QIDQ4781926

Koji Tsuda, Motoaki Kawanabe, Sören Sonnenburg, Gunnar Rätsch, Klaus-Robert Müller

Publication date: 10 December 2002

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/08997660260293274

zbMATH Keywords

classificationexponential familieskernel functionsFisher kernelprotein dataTOP kernel

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)

Related Items

Dealing with large diagonals in kernel matrices, Asymptotic Properties of the Fisher Kernel, Stochastic feature mapping for PAC-Bayes classification, VC dimension and inner product space induced by Bayesian networks, Improved learning of Riemannian metrics for exploratory analysis

Cites Work

• Soft margins for AdaBoost