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AAAI
2007
15 years 3 months ago
Manifold Denoising as Preprocessing for Finding Natural Representations of Data
A natural representation of data is given by the parameters which generated the data. If the space of parameters is continuous, then we can regard it as a manifold. In practice, w...
Matthias Hein, Markus Maier
APBC
2003
128views Bioinformatics» more  APBC 2003»
15 years 2 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
86
Voted
JMIV
2008
119views more  JMIV 2008»
15 years 24 days ago
An Improved Hybrid Model for Molecular Image Denoising
Abstract In this paper an improved hybrid method for removing noise from low SNR molecular images is introduced. The method provides an improvement over the one suggested by Jian L...
Jeny Rajan, K. Kannan, M. R. Kaimal
89
Voted
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 23 days ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
115
Voted
SIMPRA
2008
125views more  SIMPRA 2008»
15 years 22 days ago
Identification of Wiener models using optimal local linear models
The Wiener model is a versatile nonlinear block oriented model structure for miscellaneous applications. In this paper a method for identifying the parameters of such a model usin...
Martin Kozek, Sabina Sinanovic