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» A Boosting Approach to Multiple Instance Learning
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CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 9 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
EMNLP
2009
13 years 5 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
AIPS
2010
13 years 8 months ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
ECML
2004
Springer
14 years 1 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
ECCV
2008
Springer
14 years 9 months ago
Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation
Abstract. Tree-structured models have been widely used for human pose estimation, in either 2D or 3D. While such models allow efficient learning and inference, they fail to capture...
Greg Mori, Yang Wang 0003