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AAAI
2007
13 years 10 months ago
Semi-Supervised Learning with Very Few Labeled Training Examples
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang
ICARIS
2009
Springer
14 years 2 months ago
An Error Propagation Algorithm for Ad Hoc Wireless Networks
Abstract. We were inspired by the role of co-stimulation in the Biological immune system (BIS). We propose and evaluate an algorithm for energy efficient misbehavior detection in a...
Martin Drozda, Sven Schaust, Sebastian Schildt, He...
ISCAS
2008
IEEE
136views Hardware» more  ISCAS 2008»
14 years 1 months ago
Spatial-temporal consistent labeling for multi-camera multi-object surveillance systems
Abstract—For an intelligent multi-camera multi-object surveillance system, object correspondence across time and space is important to many smart visual applications. In this pap...
Jing-Ying Chang, Tzu-Heng Wang, Shao-Yi Chien, Lia...
CVPR
2008
IEEE
14 years 9 months ago
Two-Dimensional Active Learning for image classification
In this paper, we propose a two-dimensional active learning scheme and show its application in image classification. Traditional active learning methods select samples only along ...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang,...
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 8 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor