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» Learning to learn with the informative vector machine
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ESANN
2007
15 years 7 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
KI
2009
Springer
16 years 21 days ago
Machine Learning Techniques for Selforganizing Combustion Control
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...
ILP
2007
Springer
16 years 9 days ago
A Phase Transition-Based Perspective on Multiple Instance Kernels
: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
Romaric Gaudel, Michèle Sebag, Antoine Corn...
ECTEL
2007
Springer
16 years 10 days ago
Integration in Generic Tool Learning Design to Support Complex Learning Methodologies
: Current learning modelling languages do not allow formalization of scripts where generic tools are required. This limitation is especially relevant on remote courses when using c...
Luis de la Fuente Valentín
DSMML
2004
Springer
15 years 11 months ago
SVM Based Learning System for Information Extraction
Abstract. We present an SVM-based learning algorithm for information extraction, including experiments on the influence of different algorithm settings. Our approach needs fewer ...
Yaoyong Li, Kalina Bontcheva, Hamish Cunningham