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» Learning Optimal Parameters in Decision-Theoretic Rough Sets
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ICPR
2006
IEEE
14 years 9 months ago
Detection of presynaptic terminals on dendritic spines in double labeling confocal images
For the analysis of learning processes and the underlying changes of the shape of excitatory synapses (spines), 3-D volume samples of selected dendritic segments are scanned by a ...
Andreas Herzog, Bernd Michaelis, Gerald Krell, Kat...
IJAR
2010
130views more  IJAR 2010»
13 years 7 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
COLT
2003
Springer
14 years 1 months ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
ICRA
2002
IEEE
105views Robotics» more  ICRA 2002»
14 years 1 months ago
Learning Behavioral Parameterization using Spatio-Temporal Case-Based Reasoning
This paper presents an approach to learning an optimal behavioral parameterization in the framework of a Case-Based Reasoning methodology for autonomous navigation tasks. It is ba...
Maxim Likhachev, Michael Kaess, Ronald C. Arkin
AIME
2009
Springer
14 years 1 months ago
Prediction of Mechanical Lung Parameters Using Gaussian Process Models
Abstract. Mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. We introduce a Machine Learning approach to predict the pressure-dependent...
Steven Ganzert, Stefan Kramer, Knut Möller, D...