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ICANN
2001
Springer
14 years 1 months ago
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubi...
CVPR
2004
IEEE
14 years 11 months ago
Cue Integration through Discriminative Accumulation
Object recognition systems aiming to work in real world settings should use multiple cues in order to achieve robustness. We present a new cue integration scheme which extends the...
Maria-Elena Nilsback, Barbara Caputo
ICML
2003
IEEE
14 years 9 months ago
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Gavin Brown, Jeremy L. Wyatt
BIOCOMP
2006
13 years 10 months ago
Using Neural Nets to Estimate Evolutionary Parameters
- The rapid growth in the amount of molecular genetic data being collected will, in many cases, require the development of new analytic methods for the analysis of that data. In th...
Chi-Chiang Lee, Paul Marjoram
SCAI
2008
13 years 10 months ago
Defect Prediction in Hot Strip Rolling Using ANN and SVM
One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...