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JMLR
2006
99views more  JMLR 2006»
15 years 3 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
121
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INFSOF
2002
108views more  INFSOF 2002»
15 years 3 months ago
Architectural styles for distributed processing systems and practical selection method
The software architecture of a system has influences against various software characteristics of the system such as efficiency, reliability, maintainability, and etc.. For support...
Yoshitomi Morisawa, Katsuro Inoue, Koji Torii
ICCV
2011
IEEE
14 years 5 months ago
Segmentation as Selective Search for Object Recognition
Software available at http://disi.unitn.it/~uijlings or http://koen.me/research/ For object recognition, the current state-of-the-art is based on exhaustive search. However, to ...
K van de Sande, J Uijlings, T Gevers, A Smeulders
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 3 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider

Publication
179views
15 years 7 months ago
AutoSelect: What You Want Is What You Get Real-Time Processing of Visual Attention and Affect
While objects of our focus of attention (“where we are looking at”) and accompanying affective responses to those objects is part of our daily experience, little research exis...
Nikolaus Bee, Helmut Prendinger, Arturo Nakasone, ...