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CVPR
2005
IEEE
16 years 5 months ago
Semi-Supervised Cross Feature Learning for Semantic Concept Detection in Videos
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
Rong Yan, Milind R. Naphade
FOCS
1999
IEEE
15 years 7 months ago
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
Rosa I. Arriaga, Santosh Vempala
COGSCI
2008
129views more  COGSCI 2008»
15 years 3 months ago
A Rational Analysis of Rule-Based Concept Learning
We propose a new model of human concept learning that provides a rational analysis for learning of feature-based concepts. This model is built upon Bayesian inference for a gramma...
Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldma...
EPIA
2003
Springer
15 years 8 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas
ECML
1997
Springer
15 years 7 months ago
Constructing Intermediate Concepts by Decomposition of Real Functions
In learning from examples it is often useful to expand an attribute-vector representation by intermediate concepts. The usual advantage of such structuring of the learning problemi...
Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Brat...