2012 |
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39 | Tele Hao, Tapani Raiko, Alexander Ilin, and Juha Karhunen. Gated Boltzmann machine in texture modeling. In Artificial Neural Networks and Machine Learning - ICANN 2012, volume 7553 of Lecture Notes in Computer Science, pages 124–131. Springer, September 2012. |
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38 | KyungHyun Cho, Alexander Ilin, and Tapani Raiko. Tikhonov-type regularization for restricted Boltzmann machines. In Artificial Neural Networks and Machine Learning - ICANN 2012, volume 7552 of Lecture Notes in Computer Science, pages 81–88. Springer, 2012. |
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37 | Jaakko Luttinen and Alexander Ilin. Efficient Gaussian process inference for short-scale spatio-temporal modeling. In JMLR Workshop and Conference Proceedings (AISTATS 2012), volume 22, pages 741–750, 2012. |
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36 | Jaakko Luttinen, Alexander Ilin, and Juha Karhunen. Bayesian robust PCA of incomplete data. Neural Processing Letters, 32(2):189–202, 2012. |
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35 | Janne Hakkarainen, Alexander Ilin, Antti Solonen, Marko Laine, Heikki Haario, Johanna Tamminen, Erkki Oja, and Heikki Järvinen. On closure parameter estimation in chaotic systems. Nonlinear Processes in Geophysics, 19(-):127–143, 2012. |
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2011 |
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34 | KyungHyun Cho, Tapani Raiko, and Alexander Ilin. Gaussian-Bernoulli deep Boltzmann machine. In Proceedings of the NIPS workshop on Deep Learning and Unsupervised Feature Learning, Sierra Nevada, Spain, December 2011. |
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33 | József Hegedüs, Yoan Miche, Alexander Ilin, and Amaury Lendasse. Methodology for behavioral-based malware analysis and detection using random projections and k-nearest neighbors classifiers. In Proceedings of the 7th International Conference on Computational Intelligence and Security (CIS2011), Sanya, China, December 2011. |
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32 | József Hegedüs, Yoan Miche, Alexander Ilin, and Amaury Lendasse. Random projection method for scalable malware classification. In 14th International Symposium on Recent Advances in Intrusion Detection, California, USA, September 2011. |
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31 | KyungHyun Cho, Alexander Ilin, and Tapani Raiko. Improved learning of gaussian-bernoulli restricted boltzmann machines. In Proceedings of the International Conference on Artificial Neural Networks (ICANN 2011), Espoo, Finland, June 2011. |
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30 | Tapani Raiko, KyungHyun Cho, and Alexander Ilin. Enhanced gradient for learning boltzmann machines (abstract). In The Learning Workshop, Fort Lauderdale, Florida, April 2011. |
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29 | Tapani Raiko, KyungHyun Cho, and Alexander Ilin. Derivations of the enhanced gradient for the Boltzmann machine. Technical Report TKK-ICS-R37, Aalto University, TKK Reports in Information and Computer Science, Espoo, Finland, 2011. |
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28 | KyungHyun Cho, Tapani Raiko, and Alexander Ilin. Enhanced gradient and adaptive learning rate for training restricted boltzmann machines. In Proceedings of the International conference on machine learning (ICML 2011), Bellevue, Washington, USA, 2011. |
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2010 |
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27 | Alexander Ilin and Tapani Raiko. Practical approaches to principal component analysis in the presence of missing values. Journal of Machine Learning Research (JMLR), 11:1957–2000, July 2010. |
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26 | KyungHyun Cho, Tapani Raiko, and Alexander Ilin. Parallel tempering is efficient for learning restricted boltzmann machines. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), pages 1–8, Barcelona, Spain, July 2010. |
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25 | Jaakko Luttinen and Alexander Ilin. Transformations in variational Bayesian factor analysis to speed up learning. Neurocomputing, 73(7-9):1093–1102, 2010. |
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24 | Heikki Järvinen, Petri Räisänen, Marko Laine, Johanna Tamminen, Alexander Ilin, Erkki Oja, Antti Solonen, and Heikki Haario. Estimation of ECHAM5 climate model closure parameters with adaptive MCMC. Atmospheric Chemistry and Physics Discussion, 10:11951–11973, 2010. |
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2009 |
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23 | Laszlo Kozma, Alexander Ilin, and Tapani Raiko. Binary principal component analysis in the Netflix collaborative filtering task. In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, Grenoble, France, September 2009. |
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22 | Alexander Ilin and Alexey Kaplan. Bayesian PCA for reconstruction of historical sea surface temperatures. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2009), pages 1322–1327, Atlanta, USA, June 2009. |
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21 | Jaakko Luttinen, Alexander Ilin, and Tapani Raiko. Transformations for variational factor analysis to speed up learning. In Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN 2009), pages 77–82, Bruges, Belgium, April 2009. |
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20 | Jaakko Luttinen, Alexander Ilin, and Juha Karhunen. Bayesian robust PCA for incomplete data. In Proceedings of the 8th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2009), pages 66–73, Paraty, Brazil, March 2009. |
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19 | Jaakko Luttinen and Alexander Ilin. Variational gaussian-process factor analysis for modeling spatio-temporal data. In Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, 2009. |
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2008 |
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18 | Tapani Raiko, Alexander Ilin, and Juha Karhunen. Principal component analysis for sparse high-dimensional data. In Proceedings of the 14th International Conference on Neural Information Processing (ICONIP 2007), pages 566–575, Kitakyushu, Japan, 2008. |
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17 | Alexander Ilin and Tapani Raiko. Practical approaches to principal component analysis in the presence of missing values. Technical Report TKK-ICS-R6, Helsinki University of Technology, TKK reports in information and computer science, Espoo, Finland, 2008. |
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2007 |
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16 | Tapani Raiko, Alexander Ilin, and Juha Karhunen. Principal component analysis for large scale problems with lots of missing values. In Proceedings of the 18th European Conference on Machine Learning (ECML 2007), pages 532–541, Warsaw, Poland, September 2007. |
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15 | Antti Honkela, Harri Valpola, Alexander Ilin, and Juha Karhunen. Blind separation of nonlinear mixtures by variational Bayesian learning. Digital Signal Processing, 17(2):914–934, 2007. |
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14 | Alexander Ilin, Harri Valpola, and Erkki Oja. Finding interesting climate phenomena by exploratory statistical techniques. In Proceedings of the Fifth Conference on Artificial Intelligence Applications to Environmental Science as part of the 87th Annual Meeting of the American Meteorological Society, San Antonio, TX, USA, January 2007. |
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2006 |
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13 | Alexander Ilin, Harri Valpola, and Erkki Oja. Extraction of components with structured variance. In Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2006), pages 10528–10535, Vancouver, Canada, July 2006. |
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12 | Alexander Ilin. Independent dynamics subspace analysis. In Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN 2006), pages 345–350, Bruges, Belgium, April 2006. |
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11 | Sergey Borisov, Alexander Ilin, Ricardo Vigário, and Erkki Oja. Comparison of bss methods for the detection of  -activity components in eeg. In Proceedings of the 6th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2006), pages 430–437, Charleston, South Carolina, USA, March 2006. |
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10 | Alexander Ilin, Harri Valpola, and Erkki Oja. Exploratory analysis of climate data using source separation methods. Neural Networks, 19(2):155–167, 2006. |
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2005 |
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9 | Alexander Ilin and Harri Valpola. On the effect of the form of the posterior approximation in variational learning of ICA models. Neural Processing Letters, 22(2):183–204, October 2005. |
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8 | Alexander Ilin and Harri Valpola. Frequency-based separation of climate signals. In Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2005), pages 519–526, Porto, Portugal, October 2005. |
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7 | Alexander Ilin, Harri Valpola, and Erkki Oja. Semiblind source separation of climate data detects El Ni no as the component with the highest interannual variability. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2005), pages 1722–1727, Montréal, Québec, Canada, August 2005. |
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6 | Sergey Borisov, Alexander Ilin, Ricardo Vigário, and A. Kaplan. Source localization of low- and high-amplitude alpha activity: A segmental and DSS analysis. In Proceedings of the 11th Annual Meeting of Organization for Human Brain Mapping, Toronto, Canada, June 2005. |
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2004 |
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5 | Alexander Ilin and Antti Honkela. Post-nonlinear independent component analysis by variational Bayesian learning. In Proceedings of the 5th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004), pages 766–773, Granada, Spain, September 2004. |
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4 | Alexander Ilin, Sophie Achard, and Christian Jutten. Bayesian versus constrained structure approaches for source separation in post-nonlinear mixtures. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2004), pages 2181–2186, Budapest, Hungary, July 2004. |
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3 | Alexander Ilin, Harri Valpola, and Erkki Oja. Nonlinear dynamical factor analysis for state change detection. IEEE Transaction on Neural Networks, 15(3):559–575, May 2004. |
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2003 |
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2 | Alexander Ilin and Harri Valpola. On the effect of the form of the posterior approximation in variational learning of ICA models. In Proceedings of the 4th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2003), pages 915–920, Nara, Japan, April 2003. |
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1 | Harri Valpola, Erkki Oja, Alexander Ilin, Antti Honkela, and Juha Karhunen. Nonlinear blind source separation by variational Bayesian learning. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E86-A(3):532–541, 2003. |
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