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BMCBI
2010
150views more  BMCBI 2010»
15 years 1 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
CORR
2010
Springer
221views Education» more  CORR 2010»
15 years 1 months ago
Reduction of Feature Vectors Using Rough Set Theory for Human Face Recognition
In this paper we describe a procedure to reduce the size of the input feature vector. A complex pattern recognition problem like face recognition involves huge dimension of input ...
Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nas...
177
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INTERSPEECH
2010
14 years 11 months ago
Memory-based active learning for French broadcast news
Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at r...
Frédéric Tantini, Christophe Cerisar...
PE
2010
Springer
124views Optimization» more  PE 2010»
14 years 11 months ago
High-level approach to modeling of observed system behavior
Current computer systems and communication networks tend to be highly complex, and they typically hide their internal structure from their users. Thus, for selected aspects of cap...
Thomas Begin, Alexandre Brandwajn, Bruno Baynat, B...
122
Voted
ICPR
2004
IEEE
16 years 5 months ago
Optimally Regularised Kernel Fisher Discriminant Analysis
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot