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ICML
2006
IEEE
15 years 10 months ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
AUSDM
2008
Springer
243views Data Mining» more  AUSDM 2008»
14 years 11 months ago
Structure-Based Document Model with Discrete Wavelet Transforms and Its Application to Document Classification
Term signal is an existing text representation that depicts a term as a vector of frequencies of occurrences in a number of user-defined partitions of a document. Although term si...
Supphachai Thaicharoen, Tom Altman, Krzysztof J. C...
CVPR
2008
IEEE
15 years 11 months ago
A mixed generative-discriminative framework for pedestrian classification
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
Markus Enzweiler, Dariu M. Gavrila
ICFCA
2009
Springer
14 years 7 months ago
A Concept Lattice-Based Kernel for SVM Text Classification
Abstract. Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can ...
Claudio Carpineto, Carla Michini, Raffaele Nicolus...
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
15 years 10 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...