Generalised coupled tensor factorisation

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Yilmaz, Y Kenan ^a   Cemgil, A Taylan ^a   Şimşekli, Umut ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO ACOUSTICS; ITERATIVE METHODS; MATRIX FACTORIZATION; MESSAGE PASSING; MUSIC;

AM GENERALS; COUPLED TENSOR FACTORISATION; DATA UPDATE; EXPONENTIAL-FAMILY DISTRIBUTION; GENERALIZED LINEAR MODEL; MESSAGE-PASSING; MULTIPLICATIVE UPDATES; STEP SIZE; TENSOR FACTORIZATION; TWEEDIE DISTRIBUTIONS;

TENSORS;

EID: 85162323716     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. A. T. Cemgil, Bayesian inference for nonnegative matrix factorisation models, Computational Intelligence and Neuroscience 2009 (2009) 1-17.
2. A. P. Singh, G. J. Gordon, A unified view of matrix factorization models, in: ECML PKDD'08, Part II, no. 5212, Springer, 2008, pp. 358-373.
3. E. Acar, T. G. Kolda, D. M. Dunlavy, All-at-once optimization for coupled matrix and tensor factorizations, CoRR abs/1105.3422. arXiv:1105.3422.
4. Q. Xu, E. W. Xiang, Q. Yang, Protein-protein interaction prediction via collective matrix factorization, in: In Proc. of the IEEE International Conference on BIBM, 2010, pp. 62-67.
5. T. G. Kolda, B.W. Bader, Tensor decompositions and applications, SIAMReview 51 (3) (2009) 455-500.
6. Y. K. Yilmaz, A. T. Cemgil, Probabilistic latent tensor factorization, in: Proceedings of the 9th international conference on Latent variable analysis and signal separation, LVA/ICA'10, Springer-Verlag, 2010, pp. 346-353.
7. C. Fevotte, A. T. Cemgil, Nonnegative matrix factorisations as probabilistic inference in composite models, in: Proc. 17th EUSIPCO, 2009.
8. Y. K. Yilmaz, A. T. Cemgil, Algorithms for probabilistic latent tensor factorization, Signal Processing( 2011),doi:10.1016/j.sigpro.2011.09.033.
9. C. E. McCulloch, S. R. Searle, Generalized, Linear, and Mixed Models, Wiley, 2001.
10. C. E. McCulloch, J. A. Nelder, Generalized Linear Models, 2nd Edition, Chapman and Hall, 1989.
11. R. Kaas, Compound poisson distributions and glm's, tweedie's distribution, Tech. rep., Lecture, Royal Flemish Academy of Belgium for Science and the Arts, (2005).
12. A. Cichocki, R. Zdunek, A. H. Phan, S. Amari, Nonnegative Matrix and Tensor Factorization, Wiley, 2009.
13. J. R. Magnus, H. Neudecker, Matrix Differential Calculus with Applications in Statistics and Econometrics, 3rd Edition, Wiley, 2007.
14. M. Wainwright, M. I. Jordan, Graphical models, exponential families, and variational inference, Foundations and Trends in Machine Learning 1 (2008) 1-305.
15. D. D. Lee, H. S. Seung, Algorithms for non-negative matrix factorization, in: NIPS, Vol. 13, 2001, pp. 556-562.
16. M. Marcus, H. Minc, A Survey of Matrix Theory and Matrix Inequalities, Dover, 1992.
17. R. Salakhutdinov, A. Mnih, Probabilistic matrix factorization, in: Advances in Neural Information Processing Systems, Vol. 20, 2008.
18. G. H. Golub, C. F. V. Loan, Matrix computations, 3rd Edition, Johns Hopkins UP, 1996.
19. P. Smaragdis, J. C. Brown, Non-negative matrix factorization for polyphonic music transcription, in: WASPAA, 2003, pp. 177-180.