Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Former Workpage of Harri Valpola

Suomeksi / This page is also available in Finnish

I'm now (again) working at ICS. See my new workpage. During 1.11.2004-30.11.2010, I worked in LCE (another lab at HUT). Have a look at my old workpage.

Former Research interests

The topic of my thesis was the application of a variational Bayesian method called ensemble learning for unsupervised learning, nonlinear factor analysis in particular.

In the past, I have applied ensemble learning for several generative models, in addition to ICA and nonlinear factor analysis for instance for sparse coding. Related Matlab packages are available at the Bayes-group homepage.

Background of my research.


List of publications

Click here for 2004 and later. Most publication from 2004 are listed below but with without links to the papers.

H. Valpola. (2004)
Behaviourally meaningful representations from normalisation and context-guided denoising, AI Lab technical report, University of Zurich.

H. Valpola and J. Särelä. (2004)
Accurate, fast and stable denoising source separation algorithms. In Proceedings of the 5th International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2004, Granada, Spain, pp. 65-72.

A. Honkela, S. Harmeling, L. Lundqvist and H. Valpola. (2004)
Using kernel PCA for initialisation of variational Bayesian nonlinear blind source separation method. In Proceedings of the 5th International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2004, Granada, Spain, pp. 65-72.

A. Honkela and H. Valpola. (2004)
Variational Learning and Bits-Back Coding: an Information Theoretic View to Bayesian Learning, IEEE Transactions on Neural Networks, 15(4), pp. 800-810.

A. Ilin, H. Valpola and E. Oja. (2004)
Nonlinear Dynamical Factor Analysis for State Change Detection, IEEE Transactions on Neural Networks, 15(3), pp. 559-575.

H. Valpola, M. Harva and J. Karhunen. (2004)
Hierarchical Models of Variance Sources, Signal Processing, 84(2), pp. 267-282.

T. Raiko, H. Valpola, T. Östman and J. Karhunen. (2003)
Missing Values in Hierarchical Nonlinear Factor Analysis. In Proceedings of ICANN/ICONIP'03, Istanbul, Turkey, pp. 185-189.
Paper: Post Script version, PDF version
Poster: Post Script version, PDF version

H. Valpola, M. Harva and J. Karhunen. (2003)
Hierarchical Models of Variance Sources. In Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, ICA 2003, Nara, Japan, pp. 83-88.
PDF version (627 kb)

H. Valpola, T. Östman and J. Karhunen. (2003)
Nonlinear Independent Factor Analysis by Hierarchical Models. In Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, ICA 2003, Nara, Japan, pp. 257-262.
PDF version (1 Mb)

A. Honkela and H. Valpola. (2003)
On-line Variational Bayesian Learning. In Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, ICA 2003, Nara, Japan, pp. 803-808.
PostScript version (160 kB), PDF version (140 kB)

A. Ilin and H. Valpola. (2003)
On the Effect of the Form of the Posterior Approximation in Variational Learning of ICA Models. In Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, ICA 2003, Nara, Japan, pp. 915-920.
Post Script version, PDF version

A. Honkela, H. Valpola and J. Karhunen. (2003)
Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches, Neural Processing Letters, 17(2), pp. 191-203.

M. Funaro, E. Oja and H. Valpola. (2003)
Independent component analysis for artefact separation in astrophysical images, Neural Networks, 16(3-4), pp. 469-478.
PDF version available at ElsevierComputerScience

H. Valpola, E. Oja, A. Ilin, A. Honkela and J. Karhunen. (2003)
Nonlinear blind source separation by variational Bayesian learning, IEICE Trans. on Fundamentals of Electronics, Communications, and Computer Sciences, E86-A(3), pp. 532-541.
PDF version

H. Valpola, A. Honkela, and J. Karhunen. (2002)
An Ensemble Learning Approach to Nonlinear Dynamic Blind Source Separation Using State-Space Models. In Proceedings of the International Joint Conference on Neural Networks (IJCNN'02), Honolulu, Hawaii, USA, pp. 460-465.
Post Script version (241 kB), PDF version (308 kB)

H. Valpola and J. Karhunen. (2002)
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models, Neural Computation 14(11), pp. 2647-2692, MIT Press.
Post Script version (654 kb) and PDF version (937 kb)
Matlab code available at the Bayes-group homepage.

H. Valpola, T. Raiko and J. Karhunen. (2001)
Building Blocks for Hierarchical Latent Variable Models. In Proceedings of the 3rd International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2001, San Diego, California, USA, pp. 716-721.
Post Script version (48 kb)

A. Iline, H. Valpola and E. Oja. (2001) Detecting Process State Changes by Nonlinear Blind Source Separation. In Proceedings of the 3rd International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2001, San Diego, California, USA, pp. 710-715.
Post Script version (152 kb) and PDF version (465 kb)

J. Särelä, H. Valpola, R. Vigário and E. Oja. (2001) Dynamical Factor Analysis of Rhythmic Magnetoencephalographic Activity. In Proceedings of the 3rd International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2001, San Diego, California, USA, pp. 457-462.

M. Funaro, E. Oja and H. Valpola. (2001) Artefact Detection in Astrophysical Image Data Using Independent Component Analysis. In Proceedings of the 3rd International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2001, San Diego, California, USA, pp. 49-54.

T. Raiko and H. Valpola. (2001) Missing Values in Nonlinear Factor Analysis. In Proceedings of the 8th International Conference on Neural Information Processing, ICONIP 2001, Shanghai, China, pp. 822-827.
Post Script version (292 kb)

K. Lagus, E. Alhoniemi and H. Valpola. (2001) Independent Variable Group Analysis. In Proceedings of International Conference on Artificial Neural Networks - ICANN 2001, Vienna, Austria, pp. 203-210.
Post Script version (69 kb)

H. Valpola, A. Honkela and J. Karhunen. (2001) Nonlinear Static and Dynamic Blind Source Separation Using Ensemble Learning. In Proc. of the Int. Joint Conf. on Neural Networks, IJCNN'01, Washington D.C., USA, pp. 2750-2755.

H. Valpola. (2001) Learning hidden dynamical systems. Learning workshop, Snowbird, Utah, USA.

X. Giannakopoulos and H. Valpola. (2001) Nonlinear Dynamical Factor Analysis. In Proceedings of The Twentieth International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2000, Paris, France, pp. 305-317.
Post Script version (422 kb)

H. Valpola. (2000) Bayesian Ensemble Learning for Nonlinear Factor Analysis. PhD thesis, Helsinki University of Technology, Espoo. Published in Acta Polytechnica Scandinavica, Mathematics and Computing Series No. 108.
Post Script version (1.5 Mb)

H. Valpola. (2000) Unsupervised Learning of Nonlinear Dynamic State-Space Models, Publications in Computer and Information Science A59, Helsinki University of Technology, Espoo, Finland.
Post Script version (341 kb)

H. Valpola, X. Giannakopoulos, A. Honkela and J. Karhunen. (2000) Nonlinear Independent Component Analysis Using Ensemble Learning: Experiments and Discussion. In Proceedings of the Second International Workshop on Independent Component Analysis and Blind Signal Separation, ICA 2000, Helsinki, Finland, pp. 351-356.
Post Script version (386 kb)

H. Valpola. (2000) Nonlinear Independent Component Analysis Using Ensemble Learning: Theory. In Proceedings of the Second International Workshop on Independent Component Analysis and Blind Signal Separation, ICA 2000, Helsinki, Finland, pp. 251-256.
Post Script version (63 kb)

H. Valpola and P. Pajunen. (2000) Fast Algorithms for Bayesian Independent Component Analysis. In Proceedings of the Second International Workshop on Independent Component Analysis and Blind Signal Separation, ICA 2000, Helsinki, Finland, pp. 233-237.
Post Script version (167 kb)

(Note: Lappalainen = nowadays Valpola.)

H. Lappalainen, A. Honkela, X. Giannakopoulos and J. Karhunen. (2000) Nonlinear Source Separation Using Ensemble Learning and MLP Networks, to appear in Proceedings of the Symposium 2000 on Adaptive Systems for Signal Processing, Communications, and Control, AS-SPCC, Lake Louise, Alberta, Canada, October 1-4.
Post Script version (367 kb)

H. Lappalainen and A. Honkela. (2000) Bayesian Nonlinear Independent Component Analysis by Multi-Layer Perceptrons. In M. Girolami, editor, Advances in Independent Component Analysis, pp. 93-121, Springer-Verlag.
Post Script version (420 kb)

H. Lappalainen and J. W. Miskin. (2000) Ensemble Learning. In M. Girolami, editor, Advances in Independent Component Analysis, pp. 75-92, Springer-Verlag.
Post Script version (127 kb)

H. Lappalainen. (1999) Fast Fixed-Point Algorithms for Bayesian Blind Source Separation, Publications in Computer and Information Science A56, Helsinki University of Technology, Espoo, Finland.
Post Script version (277 kb)

H. Lappalainen, X. Giannakopoulos and J. Karhunen. (1999) Nonlinear Blind Source Separation Using Ensemble Learning. Presented at Snowbird Learning Workshop.
Post Script version (38 kb)

H. Lappalainen and X. Giannakopoulos. (1999) Multi-Layer Perceptrons as Nonlinear Generative Models for Unsupervised Learning: a Bayesian Treatment. In Proceedings of the ICANN'99, Edinburgh, Scotland, pp. 19-24.
Post Script version (126 kb)

H. Lappalainen. (1999) Ensemble Learning for Independent Component Analysis. In Proceedings of the First International Workshop on Independent Component Analysis and Blind Signal Separation, ICA'99, Aussois, France, pp. 7-12.
Post Script version (90 kb)

H. Lappalainen. (1998) Using an MDL-based cost function with neural networks. In Proceedings of the IJCNN'98, Anchorage, pp. 2384-2389.
Comments, Post Script version (63 kb)

T. Kohonen, S. Kaski, and H. Lappalainen. (1997) Self-organized formation of various invariant-feature filters in the Adaptive-Subspace SOM. Neural Computation, 9(6), pp. 1321-1344.
Post Script version (246 kb)

T. Kohonen, S. Kaski, H. Lappalainen, and J. Salojärvi. (1997) The Adaptive-Subspace Self-Organizing Map (ASSOM). Workshop on Self-Organizing Maps (WSOM'97), Espoo, Finland, pp. 191-196.

H. Lappalainen. (1996) Soft multiple winners for sparse feature extraction. In Proceedings of the ICNN'96, Washington, pp. 207-210.
Post Script version (196 kb)

S. Laine, H. Lappalainen, and S.-L. Jämsä-Jounela. (1995) On-line determination of ore type using cluster analysis and neural networks. Minerals Engineering, 8(6), pp. 637-648.


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