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ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 7 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
ICALT
2009
IEEE
14 years 2 months ago
Towards a Unified Format for Describing Teaching Methods
This paper reports developments on a best description template for teaching methods, whose descriptive elements will eventually be mapped to the elements of the IMS Learning Desig...
Michael Derntl, Susanne Neumann, Petra Oberhuemer
SEMWEB
2005
Springer
14 years 1 months ago
Bootstrapping Ontology Alignment Methods with APFEL
Abstract. Ontology alignment is a prerequisite in order to allow for interoperation between different ontologies and many alignment strategies have been proposed to facilitate the ...
Marc Ehrig, Steffen Staab, York Sure
CIDM
2009
IEEE
14 years 2 months ago
Diversity analysis on imbalanced data sets by using ensemble models
— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
Shuo Wang, Xin Yao
ACCV
2009
Springer
13 years 12 months ago
Efficient Classification of Images with Taxonomies
We study the problem of classifying images into a given, pre-determined taxonomy. The task can be elegantly translated into the structured learning framework. Structured learning, ...
Alexander Binder, Motoaki Kawanabe, Ulf Brefeld