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» Top-k learning to rank: labeling, ranking and evaluation
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ECCV
2010
Springer
15 years 2 days ago
Bilinear Kernel Reduced Rank Regression for Facial Expression Synthesis
In the last few years, Facial Expression Synthesis (FES) has been a flourishing area of research driven by applications in character animation, computer games, and human computer ...
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
15 years 3 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
JUCS
2010
217views more  JUCS 2010»
14 years 8 months ago
The 3A Personalized, Contextual and Relation-based Recommender System
Abstract: This paper discusses the 3A recommender system that targets CSCL (computersupported collaborative learning) and CSCW (computer-supported collaborative work) environments....
Sandy El Helou, Christophe Salzmann, Denis Gillet
MM
2006
ACM
181views Multimedia» more  MM 2006»
15 years 3 months ago
Towards content-based relevance ranking for video search
Most existing web video search engines index videos by file names, URLs, and surrounding texts. These types of video roughly describe the whole video in an abstract level without ...
Wei Lai, Xian-Sheng Hua, Wei-Ying Ma
IPM
2008
100views more  IPM 2008»
14 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...