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» Learning Patterns in Noisy Data: The AQ Approach
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TKDE
2011
186views more  TKDE 2011»
13 years 3 months ago
Discovering Activities to Recognize and Track in a Smart Environment
—The machine learning and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals expe...
Parisa Rashidi, Diane J. Cook, Lawrence B. Holder,...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 8 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
14 years 4 days ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles
UM
2009
Springer
14 years 3 months ago
Predicting Customer Models Using Behavior-Based Features in Shops
Abstract. Recent sensor technologies have enabled the capture of users’ behavior data. Given the large amount of data currently available from sensor-equipped environments, it is...
Junichiro Mori, Yutaka Matsuo, Hitoshi Koshiba, Ke...
TCSV
2008
195views more  TCSV 2008»
13 years 8 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...