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» Making inferences with small numbers of training sets
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MM
2005
ACM
160views Multimedia» more  MM 2005»
14 years 2 months ago
Putting active learning into multimedia applications: dynamic definition and refinement of concept classifiers
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
Ming-yu Chen, Michael G. Christel, Alexander G. Ha...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 9 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
ECCV
2002
Springer
14 years 10 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 9 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
ENGL
2007
100views more  ENGL 2007»
13 years 8 months ago
Utilizing Computational Intelligence to Assist in Software Release Decision
—Defect tracking using computational intelligence methods is used to predict software readiness in this study. By comparing predicted number of faults and number of faults discov...
Tong-Seng Quah, Mie Mie Thet Thwin