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» Unsupervised feature selection using a neuro-fuzzy approach
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ICANN
2009
Springer
15 years 6 months ago
Using Kernel Basis with Relevance Vector Machine for Feature Selection
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
Frederic Suard, David Mercier

Publication
335views
13 years 2 months ago
Person Re-Identification: What Features are Important?
State-of-the-art person re-identi cation methods seek robust person matching through combining various feature types. Often, these features are implicitly assigned with a single ve...
Chunxiao Liu, Shaogang Gong, Chen Change Loy, Xing...
PAMI
2010
185views more  PAMI 2010»
14 years 10 months ago
Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...
Petr Somol, Jana Novovicová
CIKM
2009
Springer
15 years 6 months ago
Feature selection for ranking using boosted trees
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
ICASSP
2011
IEEE
14 years 3 months ago
Constrained discriminative mapping transforms for unsupervised speaker adaptation
Discriminative mapping transforms (DMTs) is an approach to robustly adding discriminative training to unsupervised linear adaptation transforms. In unsupervised adaptation DMTs ar...
Langzhou Chen, Mark J. F. Gales, K. K. Chin