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» Learning from Multiple Sources of Inaccurate Data
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CVPR
2008
IEEE
15 years 3 months ago
Joint multi-label multi-instance learning for image classification
In real world, an image is usually associated with multiple labels which are characterized by different regions in the image. Thus image classification is naturally posed as both ...
Zheng-Jun Zha, Xian-Sheng Hua, Tao Mei, Jingdong W...
SOCRATES
2008
151views Education» more  SOCRATES 2008»
15 years 4 months ago
Learning Translation Strategies in a CSCL Framework
This study investigated the extent to which the social constructivist approach can be applied to the teaching/learning of translation strategies in an e-learning environment. To a...
Viviana Gaballo
118
Voted
AAAI
2004
15 years 4 months ago
Learning and Inferring Transportation Routines
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Lin Liao, Dieter Fox, Henry A. Kautz
110
Voted
JMLR
2010
117views more  JMLR 2010»
14 years 10 months ago
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Xinhua Zhang, Thore Graepel, Ralf Herbrich
CVPR
2011
IEEE
14 years 11 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer