LearningCoefficient-RLCT-ofNMF

Numerical Experiment MATLAB Codes for calculating real log canonical threshold (Bayesian generalization error) for NMF.

# LearningCoefficient-RLCT-ofNMF
Numerical Experiment MATLAB Codes for calculating real log canonical threshold (Bayesian generalization error) for NMF.

This experiment had been carried out for \[Hayashi, 2017b\].

## Research
See http://nhayashi.main.jp/publications-e.html

## References
* \[Aoyagi, 2005\]: Miki Aoyagi. Sumio Watanabe. "Stochastic Complexities of Reduced Rank Regression in Bayesian Estimation", Neural Networks, 2005, No. 18, pp.924-933.
* \[Hayashi, 2017a\]: Naoki Hayashi, Sumio Watanabe. "Upper Bound of Bayesian Generalization Error in Non-Negative Matrix Factorization", Neurocomputing, Volume 266C, 29 November 2017, pp.21-28. doi: 10.1016/j.neucom.2017.04.068. (2016/12/13 submitted. 2017/8/7 published on web).
* \[Hayashi, 2017b\]: Naoki Hayashi, Sumio Watanabe. "Tighter Upper Bound of Real Log Canonical Threshold of Non-negative Matrix Factorization and its Application to Bayesian Inference." 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), Honolulu, Hawaii, USA. Nov. 27 - Dec 1, 2017. (2017/11/28).