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» A selective sampling approach to active feature selection
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IJCAI
2007
14 years 11 months ago
Common Sense Based Joint Training of Human Activity Recognizers
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however,...
Shiaokai Wang, William Pentney, Ana-Maria Popescu,...
INFOCOM
2006
IEEE
15 years 3 months ago
Sampling Techniques for Large, Dynamic Graphs
— Peer-to-peer systems are becoming increasingly popular, with millions of simultaneous users and a wide range of applications. Understanding existing systems and devising new pe...
Daniel Stutzbach, Reza Rejaie, Nick G. Duffield, S...
NIPS
2007
14 years 11 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
ICPR
2004
IEEE
15 years 11 months ago
A Fast Discriminant Approach to Active Object Recognition and Pose Estimation
This paper presents a new criterion for viewpoint selection in the context of active Bayesian object recognition and pose estimation. Recognition is performed by probabilistically...
Catherine Laporte, Rupert Brooks, Tal Arbel
DAC
2009
ACM
15 years 4 months ago
ARMS - automatic residue-minimization based sampling for multi-point modeling techniques
This paper describes an automatic methodology for optimizing sample point selection for using in the framework of model order reduction (MOR). The procedure, based on the maximiza...
Jorge Fernandez Villena, Luis Miguel Silveira