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» Methods for boosting recommender systems
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MCS
2004
Springer
14 years 1 months ago
Experiments on Ensembles with Missing and Noisy Data
Abstract. One of the potential advantages of multiple classifier systems is an increased robustness to noise and other imperfections in data. Previous experiments on classificati...
Prem Melville, Nishit Shah, Lilyana Mihalkova, Ray...
ICDAR
2009
IEEE
14 years 2 months ago
Biometric Person Authentication Method Using Camera-Based Online Signature Acquisition
A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracki...
Daigo Muramatsu, Kumiko Yasuda, Takashi Matsumoto
ACMSE
2006
ACM
14 years 1 months ago
Support vector machines for collaborative filtering
Support Vector Machines (SVMs) have successfully shown efficiencies in many areas such as text categorization. Although recommendation systems share many similarities with text ca...
Zhonghang Xia, Yulin Dong, Guangming Xing
MICCAI
2007
Springer
14 years 8 months ago
Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree
Abstract. Automatic delineation and robust measurement of fetal anatomical structures in 2D ultrasound images is a challenging task due to the complexity of the object appearance, ...
Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dor...
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