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» Learning with Kernels and Logical Representations
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ECCV
2010
Springer
14 years 28 days ago
Improving the Fisher Kernel for Large-Scale Image Classification
Abstract. The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the context of image classification the FK was s...
JURIX
2007
14 years 10 days ago
A Modular Framework for Ontology-based Representation of Patent Information
Abstract. In this paper, we present a new ontology-based formalism for representing patent information. The framework defines concepts and relations for the major aspects of paten...
Mark Giereth, Steffen Koch, Yiannis Kompatsiaris, ...
KDD
1995
ACM
112views Data Mining» more  KDD 1995»
14 years 2 months ago
Learning First Order Logic Rules with a Genetic Algorithm
This paper introduces a newalgorithm called SIAO1 for learning first order logic rules withgenetic algorithms. SIAO1uses the covering principle developed in AQwhereseed examplesar...
Sébastien Augier, Gilles Venturini, Yves Ko...
ACL
2009
13 years 8 months ago
Learning Context-Dependent Mappings from Sentences to Logical Form
We consider the problem of learning context-dependent mappings from sentences to logical form. The training examples are sequences of sentences annotated with lambda-calculus mean...
Luke S. Zettlemoyer, Michael Collins
CVPR
2012
IEEE
12 years 1 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...