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» Machine Learning with Data Dependent Hypothesis Classes
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NIPS
2000
13 years 10 months ago
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to novelty detection provide a measure of how...
Paul Hayton, Bernhard Schölkopf, Lionel Taras...
ICML
2000
IEEE
14 years 9 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic
ICGI
1998
Springer
14 years 1 months ago
Learning Stochastic Finite Automata from Experts
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
Colin de la Higuera
ICML
2009
IEEE
14 years 9 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
BMCBI
2006
173views more  BMCBI 2006»
13 years 8 months ago
Kernel-based distance metric learning for microarray data classification
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...
Huilin Xiong, Xue-wen Chen