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» Classification with guaranteed probability of error
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CIARP
2006
Springer
13 years 11 months ago
A Theoretical Comparison of Two Linear Dimensionality Reduction Techniques
Abstract. A theoretical analysis for comparing two linear dimensionality reduction (LDR) techniques, namely Fisher's discriminant (FD) and Loog-Duin (LD) dimensionality reduci...
Luis Rueda, Myriam Herrera
LREC
2008
131views Education» more  LREC 2008»
13 years 9 months ago
Learning Morphology with Morfette
Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system i...
Grzegorz Chrupala, Georgiana Dinu, Josef van Genab...
CORR
2000
Springer
134views Education» more  CORR 2000»
13 years 7 months ago
Learning Complexity Dimensions for a Continuous-Time Control System
This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consist...
Pirkko Kuusela, Daniel Ocone, Eduardo D. Sontag
CVPR
2008
IEEE
14 years 9 months ago
Non-negative graph embedding
We introduce a general formulation, called non-negative graph embedding, for non-negative data decomposition by integrating the characteristics of both intrinsic and penalty graph...
Jianchao Yang, Shuicheng Yan, Yun Fu, Xuelong Li, ...
CVPR
2007
IEEE
14 years 9 months ago
Combining Static Classifiers and Class Syntax Models for Logical Entity Recognition in Scanned Historical Documents
Class syntax can be used to 1) model temporal or locational evolvement of class labels of feature observation sequences, 2) correct classification errors of static classifiers if ...
Song Mao, Praveer Mansukhani, George R. Thoma