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» Learning a Generative Model for Structural Representations
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ACL
2010
13 years 3 months ago
A Probabilistic Generative Model for an Intermediate Constituency-Dependency Representation
We present a probabilistic model extension to the Tesni`ere Dependency Structure (TDS) framework formulated in (Sangati and Mazza, 2009). This representation incorporates aspects ...
Federico Sangati
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
13 years 10 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
UAIS
2008
155views more  UAIS 2008»
13 years 5 months ago
Adaptive course generation through learning styles representation
This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focuse...
Enver Sangineto, Nicola Capuano, Matteo Gaeta, Ale...
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
13 years 11 months ago
Factorial representations to generate arbitrary search distributions
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Marc Toussaint
IUI
2006
ACM
13 years 11 months ago
Interactive learning of structural shape descriptions from automatically generated near-miss examples
Sketch interfaces provide more natural interaction than the traditional mouse and palette tool, but can be time consuming to build if they have to be built anew for each new domai...
Tracy Hammond, Randall Davis