Variational bayesian mixture of robust CCA models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6323 LNAI, Issue PART 3, 2010, Pages 370-385

  Viinikanoja, Jaakko ^a   Klami, Arto ^a   Kaski, Samuel ^a  

^a HELSINKI INSTITUTE FOR INFORMATION TECHNOLOGY   (Finland)

Author keywords

Bayesian data analysis; canonical correlation analysis; data fusion; latent variable models; robust models

Indexed keywords

ARTIFICIAL DATA; AUTONOMIC NERVOUS SYSTEM; BAYESIAN DATA ANALYSIS; CANONICAL CORRELATION ANALYSIS; CANONICAL CORRELATIONS; EXPLORATORY ANALYSIS; GENERATIVE MODEL; LATENT VARIABLE MODELS; NATURAL PHENOMENA; NEW MODEL; NOISY DATA; PROBABILISTIC INTERPRETATION; ROBUST MODELS; STATISTICAL DEPENDENCIES; T-DISTRIBUTION; VARIATIONAL BAYESIAN;

DATA FUSION; DATA REDUCTION; INFERENCE ENGINES; INFORMATION FUSION; LEARNING SYSTEMS;

BAYESIAN NETWORKS;

EID: 77958062608     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15939-8_24     Document Type: Conference Paper

References (18)

1. Archambeau, C., Verleysen, M.: Robust Bayesian clustering. Neural Networks 20, 129-138 (2007)
2. Archambeau, C., Delannay, N., Verleysen, M.: Robust probabilistic projections. In: Cohen, W., Moore, A. (eds.) Proceedings of ICML 2006, the 23rd International Conference on Machine Learning, pp. 33-40. ACM, New York (2006)
3. Bach, F.R., Jordan, M.I.: A probabilistic interpretation of canonical correlation analysis. Tech. Rep. 688, Department of Statistics, University of California, Berke-ley (2005)
4. Beal, M.: Variational algorithms for approximate Bayesian inference. Ph.D. thesis, Gatsby Computational Neuroscience Unit, University College London, UK (2003)
5. Chatzis, S., Kosmopoulos, D., Varvarigou, T.: Signal modeling and classification using a robust latent space model based on t distributions. IEEE Transactions on Signal Processing 56(3), 949-963 (2008)
6. Correa, N., Li, Y.O., Adali, T., Calhoun, V.D.: Canonical correlation analysis for feature-based fusion of biomedical imaging modalities to detect associative networks in schizophrenia. Special issue on fMRI analysis for Human brain mapping. IEEE J. Selected Topics in Signal Processing 2(6), 998-1007 (2008)
7. Fern, X., Brodley, C.E., Friedl, M.A.: Correlation clustering for learning mixtures of canonical correlation models. In: Kargupta, H., Kamath, C., Srivastava, J., Good-man, A. (eds.) Proceedings of the Fifth SIAM International Conference on Data Mining, pp. 439-448 (2005)
8. Gao, J.: Robust L1 principal component analysis and its Bayesian variational in-ference. Neural Computation 20(2), 555-572 (2008)
9. Hardoon, D.R., Szedmak, S., Shawe-Taylor, J.: Canonical correlation analysis: An overview with application to learning methods. Neural Computation 16(12), 2639-2664 (2004)
10. Klami, A., Kaski, S.: Local dependent components. In: Ghahramani, Z. (ed.) Proceedings of ICML 2007, the 24th International Conference on Machine Learning, pp. 425-432. Omnipress (2007)
11. Liu, C., Rubin, D.: ML estimation of the t distribution using EM and its extensions, ECM and ECME. Statistica Sinica 5, 19-39 (1995)
12. Luttinen, J., Ilin, A., Karhunen, J.: Bayesian robust PCA for incomplete data. In: Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation, pp. 66-73 (2009)
13. McLachlan, G.J., Peel, D.: Finite Mixture Models. John Wiley & Sons, New York (2000)
14. Neal, R.: Bayesian learning for neural networks. Lecture Notes in Statistics, vol. 118. Springer, New York (1996)
15. Onoda, K., Okamoto, Y., Shishida, K., Hashizume, A., Ueda, K., Yamashita, H., Yamawaki, S.: Anticipation of affective images and event-related desynchronization (ERD) of alpha activity: An MEG study. Brain Research 1151, 134-141 (2007)
16. Wang, C.: Variational Bayesian approach to canonical correlation analysis. IEEE Transactions on Neural Networks 18, 905-910 (2007)
17. Ylipaavalniemi, J., Savia, E., Malinen, S., Hari, R., Viǵario, R., Kaski, S.: Depen-dencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli. NeuroImage 48, 176-185 (2009)
18. Yokosawa, K., Pamilo, S., Hirvenkari, L., Ramkumar, P., Pihko, E., Hari, R.: Acti-vation of auditory cortex by anticipating and hearing emotional sounds: a magne-toencephalographic study. In: 16th Annual Meeting of the Organization for Human Brain Mapping (June 2010)