Changes between Version 17 and Version 18 of MatrixFactorization


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Timestamp:
07/21/11 12:50:46 (3 years ago)
Author:
MarinkaZitnik
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  • MatrixFactorization

    v17 v18  
    3535=== pmf === 
    3636Probabilistic MF. PMF model scales linearly with the number of observations and performs well on large, sparse, imbalanced datasets.[[BR]] 
    37 Reference: (Salakhutdinov, 2007). 
     37Reference: (Salakhutdinov, Mnih 2008 (NIPS)). 
    3838 
    3939=== Additional: bpmf === 
    4040Bayesian PMF model that implements Gibbs sampler. In Bayesian PMF model capacity is controlled automatically by integrating over all model parameters and hyperparameters. Bayesian PMF can be efficiently trained using MCMC methods. This model achieves significantly higher prediction accuracy than PMF models trained using MAP estimation. This algorithm has been used by winning and top ranked teams in KDD Cup 2011. [[BR]] 
    41 Reference: (Salakhutdinov, Mnih, 2008). 
     41Reference: (Salakhutdinov, Mnih, 2008 (ICML)). 
    4242 
    4343=== psmf === 
     
    137137 * Pascual-Montano, A., Carazo, J. M., Kochi, K., Lehmann, D., Pascual-Marqui, R. D. Nonsmooth nonnegative matrix factorization (nsnmf). IEEE transactions on pattern analysis and machine intelligence, 2006 28(3), 403--415. 
    138138 * Wang, Y., Turk, M. Fisher non-negative matrix factorization for learning local features, 2004. 
    139  * Salakhutdinov, R., Mnih, A. Probabilistic Matrix Factorization. Advances in Neural Information Processing Systems 20 (NIPS 2007). 
     139 * Salakhutdinov, R., Mnih, A. Probabilistic Matrix Factorization. NIPS 2008. 
    140140 * Sra, S., Dhillon, I. S. Nonnegative Matrix Approximation : Algorithms and Applications. Sciences-New York, 2006, 1--36. 
    141141 * Zhiyong Shen, Liang Du, Xukun Shen, Yidong Shen, Interval-valued Matrix Factorization with Applications, Data Mining, IEEE International Conference on, pp. 1037--1042, 2010 IEEE International Conference on Data Mining, 2010.