2012 |
21 | KyungHyun Cho, Tapani Raiko, Alexander Ilin, and Juha Karhunen. A two-stage pretraining algorithm for deep Boltzmann machines. In Proceedings of the NIPS 2012 Workshop on Deep Learning and Unsupervised Feature Learning, pages xx–xx, Lake Tahoe, Nevada, USA, December 2012. |
|
20 | KyungHyun Cho, Tapani Raiko, and Juha Karhunen. Advances in training restricted boltzmann machines (abstract), October 2012. |
|
19 | Tele Hao, Tapani Raiko, Alexander Ilin, and Juha Karhunen. Gated Boltzmann machines in texture modeling. In Artificial Neural Networks and Machine Learning - ICANN 2012, volume 7553 of Lecture Notes in Computer Science, pages 124–131, Lausanne, Switzerland, September 2012. Springer-Verlag. |
|
18 | Juha Karhunen, Tele Hao, and Jarkko Ylipaavalniemi. 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 (IJCNN2012), pages xxx–xxx, Brisbane, Australia, June 2012. IEEE. |
|
17 | Juha Karhunen, Tele Hao, and Jarkko Ylipaavalniemi. 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), volume 7191 of Lecture Notes in Computer Science, pages 91–98, Tel-Aviv, Israel, March 2012. Springer-Verlag, Berlin. |
|
16 | Jaakko Luttinen, Alexander Ilin, and Juha Karhunen. Bayesian robust PCA of incomplete data. Neural Processing Letters, 36(2):189–202, 2012. |
|
2011 |
15 | Juha Karhunen and Tele Hao. Finding dependent and independent components from two related data sets. In Proc. of the 2011 Int. Joint Conf. on Neural Networks (IJCNN2011), pages 457–466, San Jose, California, USA, August 2011. IEEE. |
|
14 | Juha Karhunen. Robust PCA methods for complete and missing data. Neural Network World, 21:357–392, 2011. |
|
2010 |
13 | Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, and Juha Karhunen. Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes. Journal of Machine Learning Research, 11:3283–3316, 2010. |
|
12 | Christian Jutten, Massoud Babaie-Zadeh, and Juha Karhunen. Chapter 14: Nonlinear mixtures. In Christian Jutten and Pierre Comon, editors, Handbook of Blind Source Separation, Independent Component Analysis and Applications, pages 549–592. Academic Press, 2010. |
|
2009 |
11 | Mikael Kuusela, Tapani Raiko, Antti Honkela, and Juha Karhunen. A gradient-based algorithm competitive with variational Bayesian EM for mixture of gaussians. In Proc. of Int. Joint Conf. on Neural Networks (IJCNN09), pages 1688–1695, Atlanta, Georgia, USA, June 2009. IEEE. |
|
10 | Jaakko Luttinen, Alexander Ilin, and Juha Karhunen. Bayesian robust PCA for incomplete data. In Proc. of the 8th Int. Conf. on Independent Component Analysis and Signal Separation (ICA 2009), volume 5441 of Lecture Notes in Computer Science, pages 66–73, Paraty, Brazil, March 2009. Springer-Verlag, Berlin. |
|
2008 |
9 | Tapani Raiko, Kai Puolamäki, Juha Karhunen, Jaakko Hollmén, Antti Honkela, Samuel Kaski, Heikki Mannila, Erkki Oja, and Olli Simula. 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. |
|
8 | Antti Honkela, Markus Harva, Tapani Raiko, and Juha Karhunen. 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. |
|
7 | Tapani Raiko, Alexander Ilin, and Juha Karhunen. Principal component analysis for sparse high-dimensional data. In Proc. of the 14th Int. Conf. on Neural Information Processing (ICONIP 2007), volume 4985 of Lecture Notes in Computer Science, pages 566–575, Kitakyushu, Japan, 2008. Springer-Verlag, Berlin. |
|
6 | Antti Honkela, Matti Tornio, Tapani Raiko, and Juha Karhunen. Natural conjugate gradient in variational inference. In Proceedings of the 14th International Conference on Neural Information Processing (ICONIP 2007), volume 4985 of Lecture Notes in Computer Science, pages 305–314, Kitakyushu, Japan, 2008. Springer-Verlag, Berlin. |
|
2007 |
5 | Tapani Raiko, Alexander Ilin, and Juha Karhunen. Principal component analysis for large scale problems with lots of missing values. In Proc. of the 18th European Conf. on Machine Learning (ECML 2007), Warsaw, Poland, September 2007. |
|
4 | Antti Honkela, Harri Valpola, Alexander Ilin, and Juha Karhunen. Blind separation of nonlinear mixtures by variational Bayesian learning. Digital Signal Processing, 17(5):914–934, 2007. |
|
3 | Tapani Raiko, Harri Valpola, Markus Harva, and Juha Karhunen. Building blocks for variational Bayesian learning of latent variable models. Journal of Machine Learning Research, 8:155–201, January 2007. |
|
2 | Juha Karhunen and Tomas Ukkonen. Extending ICA for finding jointly dependent components from two related data sets. Neurocomputing, 70(16-18):2969–2979, 2007. |
|
1 | Matti Tornio, Antti Honkela, and Juha Karhunen. Time series prediction with variational Bayesian nonlinear state-space models. In Proc. of the European Symposium on Time Series Prediction (ESTSP 2007), pages 11–19, Espoo, Finland, 2007. |
|