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» MILIS: Multiple Instance Learning with Instance Selection
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CVPR
2009
IEEE
15 years 12 days ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...
PAMI
2006
206views more  PAMI 2006»
13 years 5 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
AUSAI
2008
Springer
13 years 7 months ago
Revisiting Multiple-Instance Learning Via Embedded Instance Selection
Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learne...
James R. Foulds, Eibe Frank
ICML
2008
IEEE
14 years 6 months ago
Bayesian multiple instance learning: automatic feature selection and inductive transfer
Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Mu...