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» Computational Techniques for Modelling Learning in Economics
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CVPR
2008
IEEE
16 years 1 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 5 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 5 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
15 years 1 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
15 years 1 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