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AAAI
2006
13 years 10 months ago
A Value Theory of Meta-Learning Algorithms
We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more gene...
Abraham Bagherjeiran
CVPR
2009
IEEE
15 years 4 months ago
Learning Shape Prior Models for Object Matching
The aim of this work is to learn a shape prior model for an object class and to improve shape matching with the learned shape prior. Given images of example instances, we can le...
Cordelia Schmid, Frédéric Jurie, Tin...
ISM
2006
IEEE
377views Multimedia» more  ISM 2006»
14 years 3 months ago
Analysis of Felder-Silverman Index of Learning Styles by a Data-Driven Statistical Approach
1 In this paper a data driven analysis of FelderSilverman Index of Learning Styles (ILS) is given. Results, obtained by Multiple Correspondence Analysis and cross-validated by cor...
Silvia Rita Viola, Sabine Graf, Kinshuk, Tommaso L...
COLING
1996
13 years 10 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
ISVC
2010
Springer
13 years 7 months ago
Learning Scene Entries and Exits Using Coherent Motion Regions
We present a novel framework to reliably learn scene entry and exit locations using coherent motion regions formed by weak tracking data. We construct “entities” from weak trac...
Matthew Nedrich, James W. Davis