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» Modeling Classification and Inference Learning
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111
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ICML
2009
IEEE
15 years 7 months ago
Grammatical inference as a principal component analysis problem
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Raphaël Bailly, François Denis, Liva R...
104
Voted
COLT
2010
Springer
14 years 10 months ago
Inferring Descriptive Generalisations of Formal Languages
In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive ...
Dominik D. Freydenberger, Daniel Reidenbach
CVBIA
2005
Springer
15 years 6 months ago
A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints
In this paper we present a new framework for image segmentation using probabilistic multinets. We apply this framework to integration of regionbased and contour-based segmentation ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
101
Voted
WWW
2009
ACM
16 years 1 months ago
Inferring private information using social network data
On-line social networks, such as Facebook, are increasingly utilized by many users. These networks allow people to publish details about themselves and connect to their friends. S...
Jack Lindamood, Raymond Heatherly, Murat Kantarcio...
81
Voted
KCAP
2009
ACM
15 years 7 months ago
POIROT: acquiring workflows by combining models learned from interpreted traces
The POIROT project is a four-year effort to develop an architecture that integrates the products of a number of targeted reasoning and learning components to produce executable re...
Mark H. Burstein, Fusun Yaman, Robert Laddaga, Rob...