1224 search results - page 166 / 245 » On the Optimality of the Dimensionality Reduction Method |
167
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CVPR
2010
IEEE
15 years 11 months ago
2010
IEEE
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
167
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AAAI
2008
15 years 8 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
187
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ICASSP
2010
IEEE
15 years 6 months ago
2010
IEEE
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
172
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CORR
2010
Springer
15 years 6 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
167
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ACTAC
2006
15 years 6 months ago
2006
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...