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Selected publications

2017

Toosi, T., Sirola, M., Laukkanen, J., van Heeswijk, M., and Karhunen, J., Detecting Aging of Process Sensors with Noise Signal Measurement. To appear in Proc. of The 9th IEEE Int. Conf. on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS'2017), Bucharest, Romania, September 2017. 6 pages.

Ishikawa, S., Laaksonen, J., and Karhunen, J.,Image Pseudo Tag Generation with Deep Boltzmann Machine and Topic-Concept Similarity Match. To appear in Proc. of The Int. Joint Conf. on Neural Networks (IJCNN 2017), Anchorage, Alaska, USA, May 2017. 8 pages.

2016

Lankinen, M., Heikinheimo, H., Takala, P., Raiko, T., and Karhunen, J., A Character-Word Compositional Neural Language Model for Finnish, December 2016, 11 pages. http://arxiv.org/abs/1612.03266 .

Zhao, C., van Heeswijk, M., and Karhunen, J.,Air Quality Forecasting Using Neural Networks. In Proc. of The IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016), Athens, Greece, December 2016. 7 pages.

Sayfullina, L., Eirola, E., Komashinsky, D., Palumbo, P., and Karhunen, J., Android Malfare Detection: Building Useful Representations. In Proc. of The IEEE 15th Int. Conf. on Machine Learning and Applications (ICMLA 2016), Anaheim, California, USA, December 2016. 6 pages.

Wang, H., Raiko, T., Lensu, L., Wang, T., and Karhunen, J., Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. In Proc. of The 13th Asian Conf. on Computer Vision (ACCV 2016), Taipei, Taiwan, November 2016. 16 pages.

Grigorievskiy, A., and Karhunen, J., Gaussian Process Kernels for Popular State-Space Time Series Models. In Proc. of The Int. Joint. Conf. on Neural Networks (IJCNN 2016), Vancouver, Canada, July 2016. 10 pages. Note: IJCNN 2016 is a part of the larger conference IEEE World Congress on Computational Intelligence (IEEE WCCI 2016).

2015

Sayfullina, L., Eirola, E., Komashinsky, D., Palumbo, P., Miche, Y., Lendasse, A., and Karhunen, J. Efficient Detection of Zero-Day Android Malfare Using Normalized Bernoulli Naive Bayes. In Proc. of The 14th IEEE Int. Conf. on Trust, Security, and Privacy in Computing and Communications (IEEE TrustCom-15), Helsinki, Finland, August 2015. 8 pages.

Karhunen, J., Raiko, T., and Cho, K., Unsupervised Deep Learning: A Short Review. This paper has been published with different layout but the same contents as Chapter 7, pp. 125-142, in the book E. Bingham, S. Kaski, J. Laaksonen, and J. Lampinen (Eds.), ,Advances in Independent Component Analysis and Learning Methods, Academic Press, 2015.

Akusok, A., Miche, Y., Karhunen, J., Björk, K.-M., Nian, R., and Lendasse, A., Arbitrary Category Classification of Websites Based on Image Content. Presented in the 5th Int. Conf. on Extreme Learning Machines (ELM2014), Singapore, December 2014. Published in modified form in the IEEE Computational Intelligence Magazine, May 2015, pp. 30-41.

Juuti, M., Corona, F., and Karhunen, J., Stochastic Discriminant Analysis. In Proc. of The Int. Joint. Conf. on Neural Networks (IJCNN 2015), Killarney, Ireland, July 2015. 8 pages.

Cho, K., Raiko, T., Ilin, A., and Karhunen, J., A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. Published under the title "How to Pretrain Deep Boltzmann Machines in Two Stages" in the book P. Koprinkova-Hristova, V. Mladenov, and N. Kasabov (Eds.), Artificial Neural Networks - Methods and Applications, Springer Series in Bio-/Neuroinformatics, 2015, pp. 201-219.

Berglund, M., Raiko, T., Honkala, M., Kärkkäinen, L., Vetek, A., and Karhunen, J., Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series. To appear in Proc. of The 29th Annual Conf. on Neural Information Processing Systems (NIPS 2015), Montreal, Canada, December 2015. 9 pages.

2014

Akusok, A., Miche, Y., Karhunen, J., Björk, K.-M., Nian, R., and Lendasse, A., Arbitrary Category Classification of Websites Based on Image Content . In Proc. of the 5th Int. Conf. on Extreme Learning Machines (ELM2014), Singapore, December 2014.

Eirola, E., Lendasse, A., and Karhunen, J., Variable Selection for Regression Problems Using Gaussian Mixture Models to Estimate Mutual Information. In Proc. of the 2014 Int. Joint Conf. on Neural Networks (IJCNN 2014), pp. 1606-1613. A part of the 2014 IEEE World Congress of Computational Intelligence (WCCI 2014), Beijing, China, July 2014.

2013

Saponaro, G., Kolmonen, P., Karhunen, J., Tamminen, J., and de Leeuw, G., A Neural Network Algorithm for Cloud Fraction Estimation Using NASA-Aura OMI VIS Radiance Measurements. Atmospheric Measurement Techniques, vol. 6, 2013, pp. 2301-2309.

Karhunen, J., Hao, T., and Ylipaavalniemi, J., Finding Dependent and Independent Components from Related Data Sets: A Generalized Canonical Correlation Analysis Based Method. Neurocomputing, Vol. 113, August 2013, pp. 153-167.

Cho, K., Raiko, T., Ilin, A., and Karhunen, J., A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. In V. Mladenov et al. (Eds.), Proc. of the 2013 Int. Conf. on Artificial Neural Networks (ICANN 2013), Sofia, Bulgaria, September 2013. Lecture Notes in Computer Science, volume 8131, pages 106-113, Springer-Verlag, Berlin, 2013. A formal publication, shortened from the NIPS 2012 workshop paper.

2012

Cho, K., Raiko, T., Ilin, A., and Karhunen, J., A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. Presented in the NIPS 2012 Workshop on Deep Learning and Unsupervised Learning, Lake Tahoe, Nevada, USA, December 2012. Note that this paper is formally not a publication because the workshop did not have proceedings..

Hao, T., Raiko, T., Ilin, A., and Karhunen, J., Gated Boltzmann Machines in Texture Modeling. In Proc. of the 2012 Int. Conf. on Artificial Neural Networks (ICANN 2012), Lausanne, Switzerland, September 2012. Artificial Neural Networks and Machine Learning - ICANN 2012, Lecture Notes in Computer Science, volume 7553, pages 124-131, Springer-Verlag, Berlin, 2012.

Luttinen, J., Ilin, A., and Karhunen, J., Bayesian Robust PCA of Incomplete Data. Neural Processing Letters, Vol. 36, No. 2, June 2012, pp. 189-202.

Karhunen, J., Hao, T., and Ylipaavalniemi, J., A Generalized Canonical Correlation Analysis Based Method for Blind Source Separation from Related Data Sets. In Proc. of the 2012 Int. Joint Conf. on Neural Networks (IJCNN 2012), Brisbane, Australia, June 2012.

Karhunen, J., Hao, T., and Ylipaavalniemi, J., A Canonical Correlation Analysis Based Method for Improving BSS of Two Related Data Sets. In Proc. of the 10th Int. Conf. on Latent Variable Analysis and Signal Separation (LVA/ICA 2012), Tel-Aviv, Israel, March 2012. Lecture Notes in Computer Science, Vol. 7191, Springer-Verlag, Berlin, 2012, pp. 91-98.

2011

Karhunen, J., Robust PCA Methods for Complete and Missing Data. Neural Network World, Vol. 21, No. 5, 2011, pp. 357-392.

Karhunen, J., and Hao, T., Finding Dependent and Independent Components from Two Related Data Sets. In Proc. of the Int. Joint Conf. on Neural Networks (IJCNN 2011), San Jose, California, USA, August 2011, pp. 457-466.

2010

Honkela, A., Raiko, T., Kuusela, M., Tornio, M., and Karhunen, J., Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. Journal of Machine Learning Research, Vol. 11, November 2010, pp. 3283-3316.

Jutten, C., Babaie-Zadeh, M., and Karhunen, J., "Nonlinear Mixtures", Chapter 14, pp. 549-592, in C. Jutten and P. Comon (Eds.), Handbook of Blind Source Separation, Independent Component Analysis and Applications, Academic Press, 2010.

2009

Kuusela, M., Raiko, T., Honkela, A., and Karhunen, J., A Gradient-Based Algorithm Competitive with Variational Bayesian EM for Mixture of Gaussians. In Proc. of the IEEE 2009 Int. Conf. on Neural Networks (IJCNN2009), Atlanta, Georgia, USA, June 2009, pp. 1688--1695.

Luttinen, J., Ilin, A., and Karhunen, J., Bayesian Robust PCA for Incomplete Data. In Proc. of the 8th Int. Conf. on Independent Component Analysis and Signal Separation (ICA 2009), Paraty, Brazil, March 15-18, 2009. Published in Lecture Notes in Computer Science, vol. 5441, Springer-Verlag, 2009, pp. 66-73.

2008

Raiko, T., Ilin, A., and Karhunen, J., Principal Component Analysis for Sparse High-Dimensional Data. In Proc. of the 14th Int. Conf. on Neural Information Processing (ICONIP2007), Kitakyushu, Japan, November 13-16, 2007. Published in Lecture Notes in Computer Science, vol. 4985, Springer-Verlag, 2008, pp. 566-575.

Honkela, A., Tornio, M., Raiko, T., and Karhunen, J., Natural Conjugate Gradient in Variational Inference. In Proc. of the 14th Int. Conf. on Neural Information Processing (ICONIP2007), Special session on ``Information geometry and information theory in machine learning'', Kitakyushu, Japan, November 13-16, 2007. Published in Lecture Notes in Computer Science, vol. 4985, Springer-Verlag, 2008, pp. 305-314.

Raiko, T., Puolamäki, K., Karhunen, J., Hollmén, J., Honkela, A., Kaski, S., Mannila, H., Oja, E., and Simula, O., Macadamia: Master's Programme in Machine Learning and Data Mining. In Teaching Machine Learning: Workshop on open problems and new directions, Saint-Étienne, France, May 2008.

Honkela, A., Harva, M., Raiko, T., and Karhunen, J., Variational Inference and Learning for Continuous-Time Nonlinear State-Space Models. In Proc. of PASCAL 2008 Workshop on Approximate Inference in Stochastic Processes and Dynamical Systems, Cumberland Lodge, UK, May 2008.

2007

Raiko, T., Valpola, H., Harva, M., and Karhunen, J., Building Blocks for Variational Bayesian Learning of Latent Variable Models. Journal of Machine Learning Research, Vol. 8, January 2007, pp. 155-201.

Karhunen, J., and Ukkonen, T., Extending ICA for Finding Jointly Dependent Components from Two Related Data Sets. Neurocomputing, Vol. 70, Issues 16-18, October 2007, pp. 2969-2769. Publisher's electronic version. Note: Please use the method in my 2013 paper "Finding Dependent and Independent Components from Related Data Sets ...", it is much better than this one.

Honkela, A., Valpola, H., Ilin, A., and Karhunen, J.,, Blind Separation of Nonlinear Mixtures by Variational Bayesian Learning. Digital Signal Processing, Special issue on Bayesian Source Separation, Vol. 17, Issue 5, September 2007, pp. 914-934.

Tornio, M., Honkela, A., and Karhunen, J., Time Series Prediction with Variational Bayesian Nonlinear State-Space Models. In Proc. of the European Symp. on Time Series Prediction (ESTSP'07), Espoo, Finland, February 7-9, 2007, pp. 11-19.

Raiko, T., Ilin, A., and Karhunen, J., Principal Component Analysis for Large Scale Problems with Lots of Missing Values. In Proc. of the 12th European Conf. on Machine Learning (ECML 2007), Warsaw, Poland, September 2007, published in J. Kok et al. (Eds.), Lecture Notes in Artificial Intelligence, vol. 4701, Springer-Verlag, 2007, pp. 691-698.

2006

Karhunen, J., and Ukkonen, T., Generalizing Independent Component Analysis for Two Related Data Sets. In Proc. of the IEEE 2006 Int. Conf. on Neural Networks / 2006 IEEE World Congress on Computational Intelligence (IJCNN2006/WCCI2006), Vancouver, Canada, July 2006, pp. 1822-1829. Note: Please use the method in my 2013 paper "Finding Dependent and Independent Components from Related Data Sets ...", it is much better than this one.

Raju, K., Ristaniemi, T., Karhunen, J., and Oja, E., Jammer Suppression in DS-CDMA Arrays Using Independent Component Analysis. IEEE Trans. on Wireless Communications, Vol. 5, No. 1, January 2006, pp. 77-82.

Raiko, T., Tornio, M., Honkela, A., and Karhunen, J., State Inference in Variational Bayesian Nonlinear State-Space Models. In J. Rosca, D. Erdogmus, J. Principe, and S. Haykin (Eds.), Independent Component Analysis and Blind Signal Separation, 6th Int. Conf. (ICA2006). Lecture Notes in Computer Science, vol. 3889, Springer 2006, pp. 222-229. (Charleston, South Carolina, USA, March 5-8, 2006.)

2005

Harva, M., Raiko, T., Honkela, A., Valpola, H., and Karhunen, J., Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. In Proc. of the 21st Conf. on Uncertainty in Artificial Intelligence (UAI2005), Edinburgh, United Kingdom, July 26-29, 2005, pp. 259-266.

2004

Jutten, C., and Karhunen, J., Advances in Blind Source Separation (BSS) and Independent Component Analysis (ICA) for Nonlinear Mixtures. Int. J. Neural Systems , Vol. 14, No. 5, 2004, pp. 267-292.

Valpola, H., Harva, M, and Karhunen, J., Hierachical Models of Variance Sources. Signal Processing , Vol. 84, No. 2, February 2004, pp. 267-282.

Raju, K., Ristaniemi, T., and Karhunen, J., Semi-Blind Interference Suppression on Coherent Multipath Environments. In Proc. of the First Int. Symp. on Control, Communications, and Signal Processing (ISCCSP2004), Hammamet, Tunisia, March 21-24,2004.

2003

Jutten, C., and Karhunen, J., Advances in Nonlinear Blind Source Separation. In Proc. of the 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation (ICA2003), Nara, Japan, April 1-4, 2003, pp. 245-256.

Ristaniemi, T., Raju, K., Karhunen, J., and Oja, E., Inter-Cell Interference Cancellation in CDMA Array Systems by Independent Component Analysis. In Proc. of the 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation (ICA2003), Nara, Japan, April 1-4, 2003, pp. 739-744.

Valpola, H., Harva, M., and Karhunen, J., Hierachical Models of Variance Sources. In Proc. of the 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation (ICA2003), Nara, Japan, April 1-4, 2003, pp. 83-88.

Valpola, H., Östman, T., and Karhunen, J., Nonlinear Independent Factor Analysis by Hierarchical Models. In Proc. of the 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation (ICA2003), Nara, Japan, April 1-4, 2003, pp. 257-262.

Valpola, H., Oja, E., Ilin, A., Honkela, A., and Karhunen, J., Nonlinear Blind Source Separation by Variational Bayesian Learning. IEICE Transactions (Japan), Vol. E86-A, No. 3, March 2003, pp. 532-541.

Raiko, T., Valpola, H., Östman, T., and Karhunen, J., Missing Values in Hierarchical Nonlinear Factor Analysis. In Proc. of Int. Conf. on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP 2003), Istambul, Turkey, June 26-29, 2003, pp. 185-188.

Honkela, A., Valpola, H., and Karhunen, J., Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches. Neural Processing Latters, Vol. 17, No. 2, April 2003, pp. 191-203.

2002

Valpola, H., and Karhunen, J., An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models. Neural Computation, Vol. 14, No. 11, 2002, pp. 2647-2692.

Ristaniemi, T., Raju, K., and Karhunen, J., Jammer Mitigation in DS-CDMA Array Systems Using Independent Component Analysis. In Proc. of the 2002 IEEE Int. Conf. on Communications (ICC2002), New York City, NY, USA, April 28 - May 2, 2002.

Valpola, H., Honkela, A., and Karhunen, J., An Ensemble Learning Approach to Nonlinear Dynamic Blind Source Separation Using State-Space Models. In Proc. of the Int. Joint Conf. on Neural Networks (IJCNN2002), Honolulu, Hawaii, USA, May 12-17, 2002, pp. 460-465. In the special invited session Advances on Independent Component Analysis.

Raju, K., Ristaniemi, T., Karhunen, J., and Oja, E., Suppression of Bit-Pulsed Jammer Signals in DS-CDMA Array Systems Using Independent Component Analysis. In Proc. of the 2002 IEEE Int. Symp. on Circuits and Systems (ISCAS2002), Phoenix, Arizona, USA, May 26-29, 2002, vol. I, pp. 189-192.

Ristaniemi, T., Raju, K., Karhunen, J., and Oja, E., Jammer Cancellation in DS-CDMA Arrays: Pre and Post Switching of ICA and RAKE. To appear in Proc. of the 2002 IEEE Workshop on Neural Networks for Signal Processing (NNSP02), Martigny, Switzerland, September 4-6, 2002, pp. 495-504.

2001

Hyvärinen, A., Karhunen, J., and Oja, E., Independent Component Analysis. J. Wiley 2001, 481+xxii pages. See the homepage of the book for more information and ordering instructions.

Valpola, H., Raiko, T., and Karhunen, J., Building Blocks for Hierarchical Latent Variable Models. In Proc. of the 3rd Int. Workshop on Independent Component Analysis and Signal Separation (ICA2001), San Diego, California, USA, December 9-13, 2001, pp. 710-715.

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

Karhunen, J., Nonlinear Independent Component Analysis. A review chapter in the book R. Everson and S. Roberts (Eds.), ICA: Principles and Practice. Cambridge University Press, Cambridge, UK, 2001, pp. 113-134.

2000

Karhunen, J., Malaroiu, S., and Ilmoniemi, M., Local Linear Independent Component Analysis Using Clustering.Int. Journal of Neural Systems, vol. 10, no. 6, November/December 2000, pp. 439-451.

Cristescu, R., Ristaniemi, T., Joutsensalo, J., and Karhunen, J., Blind Separation of Convolved Mixtures for CDMA Systems.In Proc. of the X European Signal Processing Conference (EUSIPCO 2000), Tampere, Finland, September 5-8, 2000, pp. 619-622.

Lappalainen, H., Honkela, A., Giannakopoulos, X., and Karhunen, J., Nonlinear Source Separation Using Ensemble Learning and MLP Networks.In Proc. of the Symposium 2000 on Adaptive Systems for Signal Processing, Communications, and Control (AS-SPCC), Lake Louise, Alberta, Canada, October 1-4, 2000, pp. 187-192.

Lappalainen, H., Giannakopoulos, X., Honkela, A., and Karhunen, J., Nonlinear Independent Component Analysis Using Ensemble Learning: Experiments and Discussion.In Proc. of the 2nd Int. Workshop on Independent Component Analysis and Blind Source Separation (ICA2000), Espoo, Finland, June 19-22, 2000, pp. 351-356.

Cristescu, R., Joutsensalo, J., Karhunen, J., and Oja, E., A Complexity Minimization Approach for Estimating Fading Gaussian Channel in CDMA Communications.In Proc. of the 2nd Int. Workshop on Independent Component Analysis and Blind Source Separation (ICA2000), Espoo, Finland, June 19-22, 2000, pp. 527-532.

Cristescu, R., Ristaniemi, T., Joutsensalo, J, and Karhunen, J., Delay Estimation in CDMA Communications Using a Fast ICA Algorithm.In Proc. of the 2nd Int. Workshop on Independent Component Analysis and Blind Source Separation (ICA2000), Espoo, Finland, June 19-22, 2000, pp. 105-110.

1999

Giannakopoulos, X., Karhunen, J., and Oja, E., An Experimental Comparison of Neural Algorithms for Independent Component Analysis and Blind Separation. Int. Journal of Neural Systems, vol. 9, no. 2, April 1999, pp. 99-114.

Cichocki, A., Karhunen, J., Kasprzak, W., and Vigario, R., Neural Networks for Blind Separation with Unknown Number of Sources. Neurocomputing, vol. 24, nos. 1-3, February 1999, pp. 55-94.

Karhunen, J., and Malaroiu, S., Locally Linear Independent Component Analysis.In Proc. of the Int. Joint Conf. on Neural Networks (IJCNN'99), July 1999, Washington D.C., USA, pp. 882-887.

Giannakopoulos, X., Karhunen, J., and Oja, E., An Experimental Comparison of Neural ICA Algorithms with Real-World Data.In Proc. of the Int. Joint Conf. on Neural Networks (IJCNN'99), July 1999, Washington D.C., USA, pp. 888-893.

Karhunen, J., and Malaroiu, S., Local Independent Component Analysis Using Clustering. In C. Jutten, J.-F. Cardoso, and P. Loubaton (Eds.), Proc. First Int. Workshop on Independent Component Analysis and Signal Separation (ICA'99), January 11 - 15, 1999, Aussois, France, pp. 43-48.

1998

Karhunen, J., Pajunen, P., and Oja, E., The Nonlinear PCA Criterion in Blind Source Separation: Relations with Other Approaches. Neurocomputing, vol. 22, November 1998, pp. 5-20.

Giannakopoulos, X., Karhunen, J., and Oja, E., An Experimental Comparison of Neural ICA Algorithms. In L. Niklasson, M. Boden, and T. Ziemke (Eds.), ICANN98 (Proc. 8th Int. Conf. on Artificial Neural Networks, Skovde, Sweden, September 2-4, 1998), Springer-Verlag, Berlin 1998, pp. 651-656.

Pajunen, P., and Karhunen, J., Least-Squares Methods for Blind Source Separation Based on Nonlinear PCA (scanned version). Int. Journal of Neural Systems, vol. 8, nos. 5 and 6, October/December 1998, pp. 601-612.

1997

Karhunen, J., Oja, E., Wang, L., Vigario, R., and Joutsensalo, J., A Class of Neural Networks for Independent Component Analysis. IEEE Transactions on Neural Networks , vol. 8, no. 3, May 1997, pp. 486-504.

Karhunen, J., Cichocki, A., Kasprzak, W., and Pajunen, P., On Neural Blind Separation with Noise Suppression and Redundancy Reductions (scanned version). Int. Journal of Neural Systems, vol. 8, no. 2, April 1997, pp. 219-237.

Pajunen, P., and Karhunen, J., A Maximum Likelihood Approach to Nonlinear Blind Source Separation. In W. Gerstner, M. Hasler, and J.-D. Nicoud (Eds.), Artificial Neural Networks - ICANN'97, Springer-Verlag, Berlin 1997, pp. 541-546.

Karhunen, J., Hyvärinen, A., Vigario, R., Hurri, J, and Oja, E., Applications of Neural Blind Source Separation to Signal and Image Processing. In Proc. IEEE 1997 Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP'97), April 21 - 24, 1997, Munich, Germany, pp. 131-134 (invited paper).

Karhunen, J., and Pajunen, P., Blind Source Separation Using Least-Squares Type Adaptive Algorithms. In Proc. IEEE 1997 Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP'97), April 21 - 24, 1997, Munich, Germany, pp. 3361-3364.

1996

Karhunen, J., Neural Approaches to Independent Component Analysis and Source Separation. In Proc. 4th European Symposium on Artificial Neural Networks (ESANN'96), April 24 - 26, 1996, Bruges, Belgium, pp. 249-266 (invited paper).

Wang. L., and Karhunen, J., A Unified Neural Bigradient Algorithm for Robust PCA and MCA (scanned version). Int. Journal of Neural Systems, vol. 7, no. 1, March 1996, pp. 53-67.

1995

Karhunen, J., and Joutsensalo, J., Generalizations of Principal Component Analysis, Optimization Problems, and Neural Networks. Neural Networks, vol. 8, no. 4, 1995, pp. 549-562.

1994

Karhunen, J., Stability of Oja's PCA Subspace Rule. Neural Computation, vol. 6, July 1994, pp. 739-747.

Karhunen, J., and Joutsensalo, J., Representation and Separation of Signals Using Nonlinear PCA Type Learning (scanned version). Neural Networks, vol. 7, no. 1, 1994, pp. 113-127.

1992

Karhunen, J., and Joutsensalo, J., Sinusoidal Frequency Estimation by Signal Subspace Approximation. IEEE Trans. on Signal Processing, vol. 40, no. 12, December 1992, pp. 2961-2972.

1985

Oja, E. and Karhunen, J., On Stochastic Approximation of the Eigenvectors and Eigenvalues of the Expectation of a Random Matrix (scanned version). Journal of Mathematical Analysis and Applications, Vol. 106, No. 1, February 1985, pp. 69-84.

Older journal papers or book chapters not available in electronic form here

Oja, E., Karhunen, J., Hyvärinen, A., Vigario, R., and Hurri, J., Neural Independent Component Analysis - Approaches and Applications. In S.-I. Amari and N. Kasabov (Eds.), Brain-Like Computing and Intelligent Information Systems, Springer-Verlag, Singapore, 1997, pp. 167-188 (invited plenary paper at ICONIP'97).

Oja, E. and Karhunen, J., An Analysis of Convergence for a Learning Version of the Subspace Method, Journal of Mathematical Analysis and Applications, Vol. 91, No. 1, January 1983, pp. 102-111.