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» On the Use of Evidence in Neural Networks
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ECCV
2000
Springer
16 years 3 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
ICPR
2006
IEEE
16 years 2 months ago
Competitive Mixtures of Simple Neurons
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...
ICPR
2004
IEEE
16 years 2 months ago
An Efficient Three-Stage Classifier for Handwritten Digit Recognition
This paper proposes an efficient three-stage classifier for handwritten digit recognition based on NN (Neural Network) and SVM (Support Vector Machine) classifiers. The classifica...
Dejan Gorgevik, Dusan Cakmakov
99
Voted
ICASSP
2009
IEEE
15 years 8 months ago
Conditional random fields for the prediction of signal peptide cleavage sites
Correct prediction of signal peptide cleavage sites has a significant impact on drug design. State-of-the-art approaches to cleavage site prediction typically use generative mode...
Man-Wai Mak, Sun-Yuan Kung
106
Voted
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
15 years 8 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson