318 search results - page 43 / 64 » Learning subspace kernels for classification |
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
JMLR
2006
13 years 7 months ago
2006
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
EMNLP
2009
13 years 5 months ago
2009
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
BMCBI
2006
13 years 7 months ago
2006
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...