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» Computational Techniques for Modelling Learning in Economics
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CVPR
2008
IEEE
15 years 11 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
MICAI
2005
Springer
15 years 3 months ago
Agent-Based Simulation Replication: A Model Driven Architecture Approach
In Multi-agent based simulation (MABS) systems, computational models are built as multi-agent systems (MAS). Replication of these models can contribute to improve the reliability o...
Candelaria Sansores, Juan Pavón
WACV
2005
IEEE
15 years 3 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
DAGM
2008
Springer
14 years 11 months ago
Learning Visual Compound Models from Parallel Image-Text Datasets
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...
ECAI
2008
Springer
14 years 11 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche