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TKDE
2010
182views more  TKDE 2010»
13 years 8 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
ICDM
2009
IEEE
169views Data Mining» more  ICDM 2009»
13 years 7 months ago
Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification
There are many clustering tasks which are closely related in the real world, e.g. clustering the web pages of different universities. However, existing clustering approaches neglec...
Quanquan Gu, Jie Zhou
JMLR
2010
206views more  JMLR 2010»
13 years 4 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
CVPR
2009
IEEE
15 years 4 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
IPMI
2007
Springer
14 years 10 months ago
Learning Best Features and Deformation Statistics for Hierarchical Registration of MR Brain Images
A fully learning-based framework has been presented for deformable registration of MR brain images. In this framework, the entire brain is first adaptively partitioned into a numbe...
Guorong Wu, Feihu Qi, Dinggang Shen