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Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts.

, , , and . Web Intelligence, page 645-649. IEEE Computer Society, (2007)

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Using Imputation Techniques to Help Learn Accurate Classifiers., , and . ICTAI (1), page 437-444. IEEE Computer Society, (2008)Imputation-boosted collaborative filtering using machine learning classifiers., , , and . SAC, page 949-950. ACM, (2008)Imputed Neighborhood Based Collaborative Filtering., , and . Web Intelligence, page 633-639. IEEE Computer Society, (2008)A Mixture Imputation-Boosted Collaborative Filter., , and . FLAIRS, page 312-316. AAAI Press, (2008)Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction., , , and . ISVC (2), volume 4842 of Lecture Notes in Computer Science, page 469-478. Springer, (2007)Collaborative Filtering for Multi-class Data Using Belief Nets Algorithms., and . ICTAI, page 497-504. IEEE Computer Society, (2006)Making an accurate classifier ensemble by voting on classifications from imputed learning sets., , and . IJIDS, 1 (3): 301-322 (2009)A Progressive Edge-Based Stereo Correspondence Method., and . ISVC (1), volume 4841 of Lecture Notes in Computer Science, page 248-257. Springer, (2007)Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts., , , and . Web Intelligence, page 645-649. IEEE Computer Society, (2007)Using Classifier-Based Nominal Imputation to Improve Machine Learning., , , and . PAKDD (1), volume 6634 of Lecture Notes in Computer Science, page 124-135. Springer, (2011)