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» Variable selection using neural-network models
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ECCV
2000
Springer
15 years 11 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn
JMLR
2010
107views more  JMLR 2010»
14 years 4 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper
ML
2000
ACM
157views Machine Learning» more  ML 2000»
14 years 9 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
ATAL
2006
Springer
15 years 1 months ago
Learning a common language through an emergent interaction topology
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Samarth Swarup, Kiran Lakkaraju, Les Gasser
TSP
2010
14 years 4 months ago
Selection policy-induced reduction mappings for Boolean networks
Developing computational models paves the way to understanding, predicting, and influencing the long-term behavior of genomic regulatory systems. However, several major challenges ...
Ivan Ivanov, Plamen Simeonov, Noushin Ghaffari, Xi...