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JMLR
2010
136views more  JMLR 2010»
13 years 2 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
ICPR
2008
IEEE
14 years 2 months ago
Fast multiple instance learning via L1, 2 logistic regression
In this paper, we develop an efficient logistic regression model for multiple instance learning that combines L1 and L2 regularisation techniques. An L1 regularised logistic regr...
Zhouyu Fu, Antonio Robles-Kelly
ICIP
2008
IEEE
14 years 9 months ago
Pedestrian detection via logistic multiple instance boosting
Pedestrian detection in still image should handle the large appearance and pose variations arising from the articulated structure and various clothing of human bodies as well as v...
Junbiao Pang, Qingming Huang, Shuqiang Jiang, Wen ...
CVPR
2007
IEEE
14 years 9 months ago
Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure
We propose a novel classification approach for automatically detecting pulmonary embolism (PE) from computedtomography-angiography images. Unlike most existing approaches that req...
Jinbo Bi, Jianming Liang
AAAI
2007
13 years 10 months ago
Multi-Label Learning by Instance Differentiation
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
Min-Ling Zhang, Zhi-Hua Zhou