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» A Theory for Memory-Based Learning
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158
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ICPR
2002
IEEE
16 years 6 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
DICTA
2007
15 years 6 months ago
The Tower of Knowledge Scheme for Learning in Computer Vision
A scheme, named tower of knowledge (ToK), is proposed for interpreting 3D scenes. The ToK encapsulates causal dependencies between object appearance and functionality. We demonstr...
Maria Petrou, Mai Xu
ICMLA
2008
15 years 6 months ago
Multi-stage Learning of Linear Algebra Algorithms
In evolving applications, there is a need for the dynamic selection of algorithms or algorithm parameters. Such selection is hardly ever governed by exact theory, so intelligent r...
Victor Eijkhout, Erika Fuentes
199
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COLT
1994
Springer
15 years 9 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
15 years 11 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang