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» Learning from Multiple Sources of Inaccurate Data
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 4 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
143
Voted
IICAI
2003
15 years 4 months ago
Machine Learning in Infrastructure Security
Abstract: Democratic societies throughout the world, it appears, are facing a new type of threat dubbed "asymmetric threat." In this new threat environment the world gove...
V. Rao Vemuri
MMM
2007
Springer
119views Multimedia» more  MMM 2007»
15 years 9 months ago
Coopetitive Multimedia Surveillance
‘Coopetitive’ interaction strategy has been shown to give better results than similar strategies like ‘only cooperation’, ‘only competition’ etc [7]. However, this has ...
Vivek K. Singh, Pradeep K. Atrey, Mohan S. Kankanh...
134
Voted
MM
2005
ACM
160views Multimedia» more  MM 2005»
15 years 9 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...
156
Voted
CVPR
2009
IEEE
16 years 10 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic