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108
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IJON
2010
181views more  IJON 2010»
15 years 2 months ago
Active learning with extremely sparse labeled examples
An active learner usually assumes there are some labeled data available based on which a moderate classifier is learned and then examines unlabeled data to manually label the mos...
Shiliang Sun, David R. Hardoon
142
Voted
PVLDB
2008
107views more  PVLDB 2008»
15 years 2 months ago
Constrained locally weighted clustering
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Hao Cheng, Kien A. Hua, Khanh Vu
219
Voted
JASIS
2010
316views more  JASIS 2010»
15 years 2 months ago
Information sources and perceived success in corporate finance
: The work of corporate finance professionals is information intensive. In spite of that the practices and motivations of their information preferences have been researched very li...
Isto Huvila
124
Voted
BMVC
2010
15 years 1 months ago
Accounting for the Relative Importance of Objects in Image Retrieval
We introduce a method for image retrieval that leverages the implicit information about object importance conveyed by the list of keyword tags a person supplies for an image. We p...
Sung Ju Hwang, Kristen Grauman
146
Voted
TSP
2010
14 years 10 months ago
Distributed sampling of signals linked by sparse filtering: theory and applications
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...