Qiu, Chengxuan, Cotch, Mary Frances, Sigurdsson, Sigurdur, Klein, Ronald, Jonasson, Fridbert, Klein, Barbara E K, ...
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www.mfpt.org NON-STATIONARY CONDITION MONITORING WITH THE AEWATT TOOLBOX (2009)
Jan Larsen, Sigurdur Sigurdsson
Abstract: We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this...
Enhanced Context Recognition by Sensitivity Pruned Vocabularies (2009)
Rasmus Elsborg Madsen, Sigurdur Sigurdsson, Lars Kai Hansen
Document categorization tasks using the “bag-ofwords” representation have been successful in instances [11]. The relatively low dimensional bag-of-words form, is well suited for machine learning...
Shanbhag, Sujata M, Schelbert, Erik B, Hsu, Li-Yueh, Cao, Jie J, Sigurdsson, Sigurdur, Arai, Andrew E
No abstract available.
Pruning The Vocabulary For Better Context Recognition (2007)
Rasmus Elsborg Madsen, Sigurdur Sigurdsson, Lars Kai Hansen, Jan Larsen
Abstract — Language independent ‘bag-of-words ’ representations are surprisingly effective for text classification. The representation is high dimensional though, containing many nonconsistent...
Sigurdsson, Gunnar, Aspelund, Thor, Chang, Milan, Jonsdottir, Birna, Sigurdsson, Sigurdur, Eiriksdottir, Gudny, ...
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Mel Frequency Cepstral Coefficients: An Evaluation of Robustness of MP3 Encoded Music (2006)
Sigurdur Sigurdsson, Kaare Br, T Petersen, Tue Lehn-schiøler
In large MP3 databases, files are typically generated with different parameter settings, i.e., bit rate and sampling rates. This is of concern for MIR applications, as encoding difference can...
Enhanced context recognition by sensitivity pruned vocabularies (2004)
Madsen, Rasmus Elsborg, Sigurdsson, Sigurdur, Hansen, Lars Kai
Language independent `bag-of-words' representations are surprisingly effective for text classification. The generic BOW approach is based on a high-dimensional vocabulary which may reduce the...
Pruning the vocabulary for better context recognition (2004)
Madsen, Rasmus Elsborg, Sigurdsson, Sigurdur, Hansen, Lars Kai, Larsen, Jan
Language independent ‘bag-of-words’ representations are surprisingly effective for text classification. The representation is high dimensional though, containing many nonconsistent words for text...
Vocabulary pruning for improved context recognition (2004)
Madsen, Rasmus Elsborg, Sigurdsson, Sigurdur, Hansen, Lars Kai, Larsen, Jan
Language independent `bag-of-words' representations are surprisingly effective for text classification. The representation is high dimensional though, containing many non-consistent words for text...
Estimating and suppressing background in Raman spectra with an artificial neural network. (2003)
Sigurdur Sigurdsson, Peter Alshede Philipsen, Monika Gniadecka, Hans Christian Wulf, Lars Kai Hansen
In this report we address the problem of skin fluorescence in feature extraction from Raman spectra of skin lesions. We apply a highly automated neural network method for suppressing skin...
On Comparison Of Adaptive Regularization Methods (2000)
Sigurdur Sigurdsson, Jan Larsen, Lars Kai Hansen
This paper investigates recently suggested adaptive regularization schemes.
Modeling text with generalizable gaussian mixtures (2000)
Lars Kai Hansen, Sigurdur Sigurdsson, Thomas Kolenda, Finn Arup Nielsen, Ulrik Kjems, Jan Larsen
We apply and discuss generalizable Gaussian mixture (GGM) models for textmining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of...
Modeling Text With Generalizable Gaussian Mixtures (1999)
Lars Kai Hansen, Sigurdur Sigurdsson, Thomas Kolenda, Finn Arup Nielsen, Ulrik Kjems, Jan Larsen
We apply and discuss generalizable Gaussian mixture (GGM) models for textmining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of...
Modeling Text With Generalizable Gaussian Mixtures (1999)
Lars Kai Hansen, Sigurdur Sigurdsson, Thomas Kolenda, Finn Arup Nielsen, Ulrik Kjems, Jan Larsen
We apply and discuss generalizable Gaussian mixture (GGM) models for textmining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of...
Fast Kalman filtering for ARMA processes : fixed point implementation / (1982)
Thesis (M.S.)--Colorado State University, 1982.