Changes between Version 16 and Version 17 of MatrixFactorization


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Timestamp:
07/21/11 11:25:09 (3 years ago)
Author:
MarinkaZitnik
Comment:

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  • MatrixFactorization

    v16 v17  
    4747=== bd === 
    4848Bayesian decomposition. A Bayesian treatment of NMF, based on a normal likelihood and exponential priors, MCMC sampling method (Gibbs) to approximate the posterior density.[[BR]] 
    49 Reference: (Schmidt, 2003). 
     49Reference: (Schmidt, 2009). 
    5050 
    5151=== icm === 
    5252Bayesian model - Iterated conditional modes (ICM) algorithm. The modes of conditional densities have closed form expressions and ICM algorithm has a low computational cost per iteration. [[BR]] 
    53 Reference: (Schmidt, 2003). 
     53Reference: (Schmidt, 2009). 
    5454 
    5555== List of algorithms for matrix factorization initialization (currently). == 
     
    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. 
    142142 * Dueck, D., Morris, Q. D., Frey, B. J. Multi-way clustering of microarray data using probabilistic sparse matrix factorization. Bioinformatics (Oxford, England), 21 Suppl 1, 2005, 144--51. 
    143  * Schmidt, M. N., Winther, O., Kai Hansen, L. Bayesian non-negative matrix factorization. Bayesian Statistics 7 (Oxford), 2003. 
     143 * Schmidt, M. N., Winther, O., Hansen L. K. Bayesian non-negative matrix factorization, Independent Component Analysis and Signal Separation, International Conference on, 2009. 
    144144 * Ochs, M. F., Kossenkov A. V. NIH Public Access. Methods, Methods Enzymol., 2009, 59--77. 
    145  * Z. Zhang, T. Li, C. H. Q. Ding, X. Zhang: Binary Matrix Factorization with Applications. ICDM 2007. 
     145 * Zhang, Z., Li, T., Ding, C. H. Q., Zhang, X. Binary Matrix Factorization with Applications. ICDM 2007. 
    146146 * Salakhutdinov, R., Mnih, A. Bayesian probabilistic matrix factorization using Markov chain Monte Carlo. ICML 2008, 880-887.