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GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
15 years 3 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...
CVPR
2010
IEEE
15 years 6 months ago
Locality-constrained Linear Coding for Image Classification
The traditional SPM approach based on bag-of-features (BoF) must use nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effec...
Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv
BMCBI
2006
153views more  BMCBI 2006»
14 years 9 months ago
Automatic document classification of biological literature
Background: Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, ...
David Chen, Hans-Michael Müller, Paul W. Ster...
SPEECH
2010
94views more  SPEECH 2010»
14 years 4 months ago
Predicting the phonetic realizations of word-final consonants in context - A challenge for French grapheme-to-phoneme converters
One of the main problems in developing a text-to-speech (TTS) synthesizer for French lies in grapheme-to-phoneme conversion. Automatic converters produce still too many errors in ...
Josafá de Jesus Aguiar Pontes, Sadaoki Furu...
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang