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TMI
2010
206views more  TMI 2010»
13 years 5 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
ICASSP
2011
IEEE
13 years 2 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
AAAI
1998
13 years 11 months ago
Feature Generation for Sequence Categorization
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedures for accurately labeling future unlabeled sequences. The choice of representat...
Daniel Kudenko, Haym Hirsh
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 10 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
BMCBI
2008
170views more  BMCBI 2008»
13 years 10 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini