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» Neural methods for non-standard data
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ICANN
2010
Springer
15 years 4 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
ICONIP
2009
15 years 1 months ago
"Dead" Chromosomes and Their Elimination in the Neuro-Genetic Stock Index Prediction System
This paper presents a method for a short-term stock index prediction. The source data comes from the German Stock Exchange (being the target market) and two other markets (Tokyo St...
Jacek Mandziuk, Marcin Jaruszewicz
ICANN
2011
Springer
14 years 7 months ago
Semi-supervised Learning for WLAN Positioning
Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a “radio map” is constructed by modeling how the signal strength measureme...
Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
ISMB
1996
15 years 5 months ago
Refining Neural Network Predictions for Helical Transmembrane Proteins by Dynamic Programming
For transmembrane proteins experimental determina-tion of three-dimensional structure is problematic. However, membrane proteins have important impact for molecular biology in gen...
Burkhard Rost, Rita Casadio, Piero Fariselli
ICIP
2006
IEEE
16 years 5 months ago
Rotational Invariance in Adaptive fMRI Data Analysis
It has previously been shown that canonical correlation analysis (CCA) works well for detecting neural activity in fMRI data. This is due to the ability of CCA to perform simultan...
Joakim Rydell, Hans Knutsson, Magnus Borga