to appear |
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44 | Mikko A. Uusitalo, Jaakko Peltonen, and Tapani Ryhänen. Machine learning: How it can help nanocomputing. Journal of Computational and Theoretical Nanoscience, to appear. |
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43 | Joni Pajarinen, Jaakko Peltonen, and Mikko A. Uusitalo. Fault tolerant machine learning for nanoscale cognitive radio. Neurocomputing, to appear. |
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42 | Samuel Kaski and Jaakko Peltonen. Dimensionality reduction for data visualization. IEEE Signal Processing Magazine, to appear. |
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2012 |
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41 | Jaakko Peltonen and Konstantinos Georgatzis. Efficient optimization for data visualization as an information retrieval task. In Ignacio Santamaría, Jerónimo Arenas-García, Gustavo Camps-Valls, Deniz Erdogmus, Fernando Pérez-Cruz, and Jan Larsen, editors, Proceedings of MLSP 2012, the 2012 IEEE International Workshop on Machine Learning for Signal Processing, page electronic proceedings, Piscataway, NJ, 2012. IEEE. |
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2010 |
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40 | Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Helena Aidos, and Samuel Kaski. Information retrieval perspective to nonlinear dimensionality reduction for data visualization. Journal of Machine Learning Research, 11:451–490, 2010. |
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39 | Jaakko Peltonen, Helena Aidos, Nils Gehlenborg, Alvis Brazma, and Samuel Kaski. An information retrieval perspective on visualization of gene expression data with ontological annotation. In Proceedings of ICASSP 2010, IEEE International Conference on Acoustics, Speech and Signal Processing, pages 2178–2181, Piscataway, NJ, 2010. IEEE. |
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38 | Juuso Parkkinen, Kristian Nybo, Jaakko Peltonen, and Samuel Kaski. Graph visualization with latent variable models. In Proceedings of MLG-2010, the Eighth Workshop on Mining and Learning with Graphs, pages 94–101, New York, NY, USA, 2010. ACM. DOI: http://doi.acm.org/10.1145/1830252.1830265. |
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37 | Jaakko Peltonen and Samuel Kaski. Generative modeling for maximizing precision and recall in information visualization. Technical Report TKK-ICS-R38, Aalto University, Department of Information and Computer Science, Espoo, Finland, 2010. |
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36 | Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, and Mikko A. Uusitalo. Efficient planning in large pomdps through policy graph based factorized approximations. In J. Balc'azar, F. Bonchi, A. Gionis, and M. Sebag, editors, Proceedings of ECML PKDD 2010, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, part III, pages 1–16, Berlin Heidelberg, 2010. Springer-Verlag. |
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35 | Jaakko Peltonen, Yusuf Yaslan, and Samuel Kaski. Relevant subtask learning by constrained mixture models. Intelligent Data Analysis, 14:641–662, 2010. |
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2009 |
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34 | Jaakko Peltonen, Helena Aidos, and Samuel Kaski. Supervised nonlinear dimensionality reduction by neighbor retrieval. In Proceedings of ICASSP 2009, the IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 1809–1812. IEEE, 2009. |
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33 | Jaakko Peltonen. Visualization by linear projections as information retrieval. In José Príncipe and Risto Miikkulainen, editors, Advances in Self-Organizing Maps (proceedings of WSOM 2009), pages 237–245, Berlin Heidelberg, 2009. Springer. |
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32 | Jaakko Peltonen, Jarkko Venna, and Samuel Kaski. Visualizations for assessing convergence and mixing of Markov chain Monte Carlo simulations. Computational Statistics and Data Analysis, 53:4453–4470, 2009. |
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31 | Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo, and Ari Hottinen. Latent state models of primary user behavior for opportunistic spectrum access. In Proceedings of the 20th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'09), pages 1267–1271. IEEE, 2009. |
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2008 |
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30 | Jaakko Peltonen, Mikko A. Uusitalo, and Joni Pajarinen. Nano-scale fault tolerant machine learning for cognitive radio. In Jose C. Principe, Deniz Erdogmus, and Tülay Adali, editors, Proceedings of the 2008 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2008), pages 163–168. IEEE, October 2008. |
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29 | Tapani Raiko and Jaakko Peltonen. Application of UCT search to the connection games of Hex, Y, *Star, and Renkula!. In Proceedings of the Finnish Artificial Intelligence Conference (SteP 2008), Espoo, Finland, August 2008. See also the associated 3D boardgame at http://www.nbl.fi/%7Enbl924/renkula/. |
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28 | Jaakko Peltonen, Yusuf Yaslan, and Samuel Kaski. Variational Bayes learning from relevant tasks only. In Learning from Multiple Sources Workshop, 13 December 2008, Whistler Canada, 2008. Proceedings at http://web.mac.com/davidrh/LMSworkshop08/Schedule.html. |
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27 | Mikko A. Uusitalo and Jaakko Peltonen. Nanocomputing with machine learning. In Nanotech Northern Europe 2008 conference and exhibition (NTNE 2008), 2008. Poster. |
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26 | Jaakko Peltonen, Yusuf Yaslan, and Samuel Kaski. Variational Bayes learning from relevant tasks only. In Learning from Multiple Sources Workshop, 13 December 2008, Whistler Canada, 2008. Proceedings at http://web.mac.com/davidrh/LMSworkshop08/Schedule.html. |
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2007 |
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25 | Merja Oja, Jaakko Peltonen, Jonas Blomberg, and Samuel Kaski. Estimating human endogeneous retrovirus activities in various tissues with a hidden Markov mixture model. In Intelligent Systems for Molecular Biology & European Conference on Computational Biology 2007 (ISMB/ECCB 2007), Vienna, Austria, July 21-25 2007. Poster. |
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24 | Merja Oja, Jaakko Peltonen, Jonas Blomberg, and Samuel Kaski. Methods for estimating human endogenous retrovirus activities from EST databases. BMC Bioinformatics, 8(Suppl 2):S11, 2007. |
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23 | Samuel Kaski and Jaakko Peltonen. Learning from relevant tasks only. Technical Report E11, Helsinki University of Technology, Laboratory of Computer and Information Science, 2007. Available at www.cis.hut.fi/Publications. |
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22 | Samuel Kaski and Jaakko Peltonen. Learning from relevant tasks only. In Joost N. Kok, Jacek Koronacki, Ramon Lopez de Mantaras, Stan Matwin, Dunja Mladeni c, and Andrzej Skowron, editors, Machine Learning: ECML 2007 (Proceedings of the 18th European Conference on Machine Learning), pages 608–615, Berlin Heidelberg, 2007. Springer-Verlag. Preprint pdf at http://www.cis.hut.fi/projects/mi/papers/ecml07.pdf. |
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21 | Jaakko Peltonen, Jacob Goldberger, and Samuel Kaski. Fast semi-supervised discriminative component analysis. In Konstantinos Diamantaras, Tülay Adali, Ioannis Pitas, Jan Larsen, Theophilos Papadimitriou, and Scott Douglas, editors, Machine Learning for Signal Processing XVII, pages 312–317. IEEE, 2007. Preprint pdf at http://www.cis.hut.fi/projects/mi/papers/mlsp07.pdf. |
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20 | Merja Oja, Jaakko Peltonen, and Samuel Kaski. A hidden Markov model for estimating retrovirus activities from expressed sequence databases. In European Conference on Computational Biology (ECCB 2006), Eilat, Israel, January 21-24 2007. Poster. |
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2006 |
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19 | Merja Oja, Jaakko Peltonen, and Samuel Kaski. Estimation of human endogenous retrovirus activities from expressed sequence databases.. In Juho Rousu, Samuel Kaski, and Esko Ukkonen, editors, Probabilistic Modeling and Machine Learning in Structural and Systems Biology. Workshop Proceedings; Tuusula, Finland, June 17-18, pages 50–54, Helsinki, Finland, 2006. University of Helsinki. |
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18 | Jaakko Peltonen and Samuel Kaski. Learning when only some of the training data are from the same distribution as test data. In NIPS 2006 workshop on Learning when test and training inputs have different distributions, 2006. Extended abstract at http://www.cis.hut.fi/projects/mi/papers/nips06_did_abstract.pdf, poster at http://www.cis.hut.fi/projects/mi/papers/nips06_did_poster.pdf. |
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17 | Jaakko Peltonen, Jacob Goldberger, and Samuel Kaski. Fast discriminative component analysis for comparing examples. In NIPS 2006 workshop on Learning to Compare Examples, 2006. Refereed extended abstract (5 pages), available at http://www.idiap.ch/lce/. |
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2005 |
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16 | Jaakko Peltonen and Samuel Kaski. Discriminative components of data. IEEE Transactions on Neural Networks, 16(1):68–83, 2005. Preprint pdf at http://www.cis.hut.fi/projects/mi/papers/tnn04_preprint.pdf. |
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2004 |
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15 | Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski. Sequential information bottleneck for finite data. In Russ Greiner and Dale Schuurmans, editors, Proceedings of ICML 2004, the Twenty-First International Conference on Machine Learning, pages 647–654, Madison, WI, 2004. Omnipress. |
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14 | Jaakko Peltonen, Arto Klami, and Samuel Kaski. Improved learning of Riemannian metrics for exploratory analysis. Neural Networks, 17:1087–1100, 2004. Preprint postscript file at http://www.cis.hut.fi/projects/mi/papers/nn04_preprint.ps.gz. |
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13 | Jaakko Peltonen. Data Exploration with Learning Metrics. PhD thesis, Helsinki University of Technology, Dissertations in Computer and Information Science, Report D7, Espoo, Finland, 2004. Award-winning: Doctoral thesis award of the Pattern Recognition Society of Finland, for the best Finnish doctoral thesis in the field of pattern recognition 2004-2005. |
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2003 |
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12 | Jarkko Venna, Samuel Kaski, and Jaakko Peltonen. Visualizations for assessing convergence and mixing of MCMC. In N. Lavrac, D. Gamberger, H. Blockeel, and L. Todorovski, editors, Proceedings of the 14th European Conference on Machine Learning (ECML 2003), pages 432–443, Berlin, 2003. Springer. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/ecml03.ps.gz. |
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11 | Samuel Kaski and Jaakko Peltonen. Informative discriminant analysis. In Tom Fawcett and Nina Mishra, editors, Proceedings of ICML-2003, the Twentieth International Conference on Machine Learning, pages 329–336, Menlo Park, CA, 2003. AAAI Press. |
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10 | Jaakko Peltonen, Arto Klami, and Samuel Kaski. Learning metrics for information visualization. In Proceedings of WSOM'03, Workshop on Self-Organizing Maps, pages 213–218, Kitakyushy, Japan, 2003. Kyushu Institute of Technology. (Proceedings on CD-ROM). |
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9 | Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski. Finite sequential information bottleneck (fsIB). Technical Report A74, Helsinki University of Technology, Publications in Computer and Information Science, Espoo, Finland, 2003. |
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2002 |
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8 | Jaakko Peltonen, Arto Klami, and Samuel Kaski. Learning more accurate metrics for self-organizing maps. In José R. Dorronsoro, editor, Artificial Neural Networks—ICANN 2002, pages 999–1004, Berlin, 2002. Springer. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/icann02.ps.gz. |
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7 | Jaakko Peltonen. Itseorganisoituvat kartat oppivissa metriikoissa. Tekniikan Akateemiset, 5/2002, 2002. |
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6 | Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski. Discriminative clustering of text documents. In Lipo Wang, Jagath C. Rajapakse, Kunihiko Fukushima, Soo-Young Lee, and Xin Yao, editors, Proceedings of ICONIP'02, 9th International Conference on Neural Information Processing, pages 1956–1960, Piscataway, NJ, 2002. IEEE. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/iconip02.ps.gz. |
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5 | Arto Klami, Jaakko Peltonen, and Samuel Kaski. Accurate self-organizing maps in learning metrics. In Pekka Ala-Siuru and Samuel Kaski, editors, Step 2002 – Intelligence, The Art of Natural and Artificial. Proceedings of the 10th Finnish Artificial Intelligence Conference, pages 41–49. Finnish Artificial Intelligence Society, 2002. |
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2001 |
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4 | Jaakko Peltonen. Self-organizing maps in learning metrics. Master's thesis, Helsinki University of Technology, Department of Engineering Physics and Mathematics, 2001. Award-winning: Master's thesis award 2002 for best Finnish Master's thesis in technology, granted by Tekniikan Akateemisten Liitto TEK ry and Tekniska Föreningen i Finland TFiF r.f. |
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3 | Samuel Kaski, Janne Sinkkonen, and Jaakko Peltonen. Data visualization and analysis with self-organizing maps in learning metrics. In Yahiko Kambayashi, Werner Winiwarter, and Masatoshi Arikawa, editors, Proceedings of DaWaK'01, Third International Conference on Data Warehousing and Knowledge Discovery, pages 162–172, Berlin, 2001. Springer. (LNCS 2114). |
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2 | Samuel Kaski, Janne Sinkkonen, and Jaakko Peltonen. Learning metrics for self-organizing maps. In Proceedings of IJCNN01, International Joint Conference on Neural Networks, pages 914–919, Piscataway, NJ, 2001. IEEE. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/ijcnn01.ps.gz. |
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1 | Samuel Kaski, Janne Sinkkonen, and Jaakko Peltonen. Bankruptcy analysis with self-organizing maps in learning metrics. IEEE Transactions on Neural Networks, 12:936–947, 2001. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/trnn00_preprint.ps.gz. |
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