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» Self-Paced Learning for Matrix Factorization
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WWW
2010
ACM
14 years 2 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
MVA
2007
154views Computer Vision» more  MVA 2007»
13 years 9 months ago
Fisher Non-negative Matrix Factorization with Pairwise Weighting
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
Xi Li, Kazuhiro Fukui
SDM
2010
SIAM
181views Data Mining» more  SDM 2010»
13 years 5 months ago
Efficient Nonnegative Matrix Factorization with Random Projections
The recent years have witnessed a surge of interests in Nonnegative Matrix Factorization (NMF) in data mining and machine learning fields. Despite its elegant theory and empirical...
Fei Wang, Ping Li
ICASSP
2008
IEEE
14 years 1 months ago
Nonnegative matrix factorization for real time musical analysis and sight-reading evaluation
Sight-reading is the ability to read and perform music from a written score with little or no preparation. Though an integral part of musicianship, it is rarely or minimally addre...
Chih-Chieh Cheng, D. Jingtong Hu, Lawrence K. Saul
ICASSP
2010
IEEE
13 years 7 months ago
Multiplicative update rules for nonnegative matrix factorization with co-occurrence constraints
Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
Steven K. Tjoa, K. J. Ray Liu