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» Structure feature selection for graph classification
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MCS
2010
Springer
13 years 7 months ago
Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems
Selecting a set of good and diverse base classifiers is essential for building multiple classifier systems. However, almost all commonly used procedures for selecting such base cla...
Wan-Jui Lee, Robert P. W. Duin, Horst Bunke
COLING
2008
13 years 7 months ago
Exact Inference for Multi-label Classification using Sparse Graphical Models
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Yusuke Miyao, Jun-ichi Tsujii
ICCV
2007
IEEE
14 years 7 months ago
Vector Quantizing Feature Space with a Regular Lattice
Most recent class-level object recognition systems work with visual words, i.e., vector quantized local descriptors. In this paper we examine the feasibility of a dataindependent ...
Tinne Tuytelaars, Cordelia Schmid
CIKM
2009
Springer
14 years 10 days ago
Graph classification based on pattern co-occurrence
Subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual p...
Ning Jin, Calvin Young, Wei Wang
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 7 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang