Lee, D.D. and Seung, H.S. (1999) Learning the Parts of Objects by Nonnegative matrix Factorization. Nature, 401, 788-791. http://dx.doi.org/10.1038/44565
 Li, S.Z., Hou, X., Zhang, H. and Cheng, Q. (2001) Learning Spatially Localized Parts-Based Representations. IEEE Conference on Computer Vision and Pattern Recognition, Kauai, 8-14 December 2001, 207-212. http://dx.doi.org/10.1109/cvpr.2001.990477
 Wang, Y., Jia, Y., Hu, C. and Turk, M. (2005) Nonnegative Matrix Factorization Framework for Face Recognition. International Journal of Pattern Recognition and Artificial Intelligence, 19, 495-511.http://dx.doi.org/10.1142/S0218001405004198
 Huang, X., Zhao, J., Ash, J. and Lai, W. (2013) Clustering Student Discussion Messages on Online Forum by Visualization and Nonnegative matrix Factorization. Journal of Software Engineering and Applications, 6, 7-12. http://dx.doi.org/10.4236/jsea.2013.67B002
 Guillamet, D., Bressan, M. and Vitria, J. (2001) A Weighted Nonnegative Matrix Factorization for Local Representations. IEEE Conference of Computer Vision and Pattern Recognition, Kauai, 8-14 December 2001, 942-947.
 Cichocki, A., Zdunek, R. and Amari, S. (2006) Csiszár’s Divergence for Nonnegative Matrix Factorization: Family of New Algorithms. Lecture Notes in Computer Science, 3889, 32-39. http://dx.doi.org/10.1007/11679363_5
 Pauca, V.P., Piper, J. and Plemmons, R.J. (2006) Nonnegative Matrix Factorization for Spectral Data Analysis. Linear Algebra and its Applications, 416, 29-47. http://dx.doi.org/10.1016/j.laa.2005.06.025
 Hamza, A.B. and Brady, D.J. (2006) Reconstruction of Reflectance Spectra Using Robust Nonnegative Matrix Factorization. IEEE Transactions on Signal Processing, 54, 3637-3642. http://dx.doi.org/10.1109/TSP.2006.879282
 Lin, C.J. (2007) Projected Gradient Methods for Nonnegative Matrix Factorization. Neural Computation, 19, 2756-2779. http://dx.doi.org/10.1162/neco.2007.19.10.2756
 Gonzales, E.F. and Zhang, Y. (2005) Accelerating the Lee-Seung Algorithm for Nonnegative Matrix Factorization. Technical Report, Department of Computational and Applied Mathematics, Rice University, Houston.
 Zdunek, R. and Cichocki, A. (2006) Nonnegative Matrix Factorization with Quasi-Newton Optimization. Lecture Notes in Computer Science, 4029, 870-879. http://dx.doi.org/10.1007/11785231_91
 Wild, S., Curry, J. and Dougherty, A. (2004) Improving Nonnegative Matrix Factorization through Structured Initialization. Pattern Recognition, 37, 2217-2232. http://dx.doi.org/10.1016/j.patcog.2004.02.013
 Wild, S., Curry, J. and Dougherty, A. (2003) Motivating Nonnegative Matrix Factorizations. Proceedings of the 8th SIAM Conference on Applied Linear Algebra, Williamsburg, 15-19 July 2003.http://www.siam.org/meetings/la03/proceedings/
 Piper, J., Pauca, J.P., Plemmons, R.J. and Giffin, M. (2004) Object Characterization from Spectral Data Using Nonnegative Factorization and Information Theory. Proceedings of the 2004 AMOS Technical Conference, Maui, 9-12 September 2004.
 Hoyer, P.O. (2002) Non-Negative Sparse Coding. Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, Martigny, Switzerland, 4-6 September 2002, 557-565. http://dx.doi.org/10.1109/nnsp.2002.1030067
 Zellner, A. (1986) On Assessing Prior Distributions and Bayesian Regression Analysis with g-Prior Distributions. In: Goel, P. and Zellner, A., Eds., Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti, Elsevier Science Publishers, Inc., New York, 233-243.
 Foster, D.P. and George, E.I. (1994) The Risk Inflation Criterion for Multiple Regression. Annals of Statistics, 22, 1947-1975. http://dx.doi.org/10.1214/aos/1176325766