Jaakko Peltonen

I am a professor of statistics (data analysis) at Tampere University, Faculty of Information Technology and Communication Sciences. Please see my webpage at Tampere University (previously here) for up-to-date information.

I continue to have strong collaboration with at Aalto University, Department of Computer Science, where I have been a visiting professor, and docent (adjunct professor) and where I have also been a PI of the Probabilistic Machine Learning research group. I was also previously an academy research fellow at the same department.

I have also previously worked at University of Sheffield, Sheffield Institute for Translational Neuroscience, with Prof. Magnus Rattray and Prof. Neil Lawrence. I am a member of the Centre of Excellence in Computational Inference Research COIN, Helsinki Institute for Information Technology HIIT, and the PASCAL2 Network of Excellence.

My research interests include probabilistic generative and information-theoretic methods and formalisms such as information retrieval based dimensionality reduction, especially for application in visualization, clustering, and bioinformatics.

Contact information


Mail address: Tampere University, Faculty of Information Technology and Communication Sciences, 33014 Tampere, Finland
Room:Tampere University, Pinni B building, room B0023
E-Mail:firstname dot lastname at tuni dot fi
Phone:+358 50 3623628
Twitter:@JaakkoTPeltonen

Positions of Trust and Expertise

I am an associate editor of Neural Processing Letters, editorial board member of Heliyon, and recently co-edited a special issue of Neurocomputing on machine learning for signal processing. I have been a program committee member for 33 conferences/workshops: DaWaK 2005-2008, the NIPS 2008 Learning from Multiple Sources Workshop, ISNN 2009, the NIPS 2009 workshop on Learning from Multiple Sources with Applications to Robotics, ISNN 2010, MLSP 2010, ISNN 2011, WSOM 2011, ICANN 2011, CIP 2012, MLSP 2012, ICANN 2012, ISNN 2012, the NC2 2012, 2013, 2014, 2015, and 2016 workshops, VAMP 2013, ICANN 2013, WSOM 2014, ESANN 2014, ICANN 2014, ESANN 2015, ICANN 2016, ESANN 2016, WSOM 2016, ICML 2016, ECML PKDD 2016, and ESANN 2017. I have been the publicity chair for AISTATS 2014, SCIA 2013, ICANN 2011 and WSOM 2011, the local publicity chair for MLSP 2010, and an organizer of the NIPS 2009 workshop on Learning from Multiple Sources with Applications to Robotics, organizer for VAMP'13, and publicity chair for the MLSS 2014 Iceland Machine Learning Summer School. I have reviewed for several journals listed below, and for 61 conferences so far (e.g. NIPS, ICML, ECML PKDD, MLSP, ICANN, ICASSP, DaWaK, Web Intelligence).

Reviewed for these journals: IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE/ACM Transactions on Computational Biology and Bioinformatics, International Journal of Neural Systems, Neural Processing Letters, IEEE Signal Processing Letters, Journal of Machine Learning Research, Neural Networks, Pattern Analysis and Applications, Neurocomputing, Machine Learning, Pattern Recognition, Information Processing & Management, PLoS ONE, IEEE Transactions on Systems, Man, and Cybernetics, part B, IEEE Transactions on Image Processing, Information Sciences, Data Mining and Knowledge Discovery, The Computer Journal

Teaching

Please see my webpage at Tampere University for up-to-date information.

In Fall 2016 I lecture the course MTTTS16 Learning from Multiple Sources and the course MTTTS11 Master's Seminar and Thesis at University of Tampere. I am also one of the two responsible professors for the International Master's Degree Programme on Computational Big Data Analytics (CBDA).

Earlier teaching:
In Spring 2016 I lectured the course MTTTS11 Master's Seminar and Thesis and the course MTTTS17 Dimensionality Reduction and Visualization At University of Tampere. In Fall 2015 I lectured the course MTTTS16 Learning from Multiple Sources and the course MTTTS11 Master's Seminar and Thesis at University of Tampere. In Spring 2015 I lectured the course MTTS1 Dimensionality reduction and visualization and the course MTTTS2 Pro gradu thesis and seminar at University of Tampere. In Spring 2014 I lectured the course T-61.2020 From Data to Knowledge Project Assignment with Amaury Lendasse at Aalto, and the courses MTTS1 Dimensionality reduction and visualization and MTTTS2 Pro gradu thesis and seminar at University of Tampere. In Fall 2014 I lectured the course MTTS1 Learning from Multiple Sources and the course MTTTS2 Pro gradu thesis and seminar at University of Tampere. In Spring 2013 lectured the course T-61.5010 Information Visualization together with Francesco Corona, and the course T-61.2020 From Data to Knowledge Project Assignment. In Fall 2013 I lectured the course T-61.3050 Machine Learning: Basic Principles together with Ritabrata Dutta, and the special course T-61.6040 Advanced Course in Information Visualization together with Kerstin Bunte and Manuel Eugster. In Autumn 2012 I lectured the special course T-61.6040 Multi-view and Multi-task Learning together with Sohan Seth. In Autumn 2010 I lectured two courses at Aalto University: T-61.3040 Statistical Modeling of Signals (also several earlier semesters; 2010 with Amaury Lendasse) and T-61.6040 Learning from Multiple Sources (with Arto Klami). Earlier I lectured the course 582480 Machine Learning in Bioinformatics at University of Helsinki. Still earlier I was course assistant for several years on the course T-61.5030 Advanced Course in Neural Computing at Helsinki University of Technology.

Students

Please see my webpage at Tampere University for up-to-date information.

Alumni:


Publications

Please see my webpage at Tampere University for up-to-date information.

Journal Publications


  1. Tuukka Ruotsalo*, Jaakko Peltonen*, Manuel J. A. Eugster, Dorota Glowacka, Patrik Floréen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. Interactive Intent Modeling for Exploratory Search. ACM Transactions on Information Systems, 36(4), article 44, October 2018. (* equal contributions) (final open access article on publisher webpages)

  2. Dominik Sacha, Michael Sedlmair, Leishi Zhang, John A. Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, and Daniel A. Keim. What You See Is What You Can Change: Human-Centered Machine Learning By Interactive Visualization. Neurocomputing, 268:164-175, 2017. (preprint pdf, final article on publisher webpages)

  3. Dominik Sacha, Leishi Zhang, Michael Sedlmair, John A. Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen North, and Daniel A. Keim. Visual interaction with dimensionality reduction: a structured literature analysis. IEEE Transactions on Visualization and Computer Graphics, 23(1): 241-250, 2016. (final article on publisher webpages)

  4. Antti Honkela*, Jaakko Peltonen*, Hande Topa, Iryna Charapitsa, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil D. Lawrence, and Magnus Rattray. Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays. Proceedings of the National Academy of Sciences of the United States of America, 112(42):13115-13120, 2015. (* A.H. and J.P. contributed equally to this work.) (final article on publisher webpages)

  5. Ali Faisal, Jaakko Peltonen, Elisabeth Georgii, Johan Rung, and Samuel Kaski. Toward computational cumulative biology by combining models of biological datasets. PLOS ONE, 9(11), 2014. (preprint pdf, final article on publisher webpages)

  6. Jaakko Peltonen and Ziyuan Lin. Information Retrieval Approach to Meta-visualization. Machine Learning, 99(2):189-229, 2015. (final article on publisher webpages)

  7. Joni Pajarinen, Ari Hottinen, and Jaakko Peltonen. Optimizing spatial and temporal reuse in wireless networks by decentralized partially observable Markov decision processes. IEEE Transactions on Mobile Computing, 13(4):866-879, 2014. (pdf on publisher pages)

  8. Ali Faisal*, Jussi Gillberg, Gayle Leen, and Jaakko Peltonen*. Transfer Learning using a Nonparametric Sparse Topic Model. Neurocomputing, 112:124-137, 2013. (* equal contributions) (final pdf on publisher pages)

  9. Gayle Leen*, Jaakko Peltonen*, and Samuel Kaski. Focused multi-task learning in a Gaussian process framework. Machine Learning, 89(1-2):157-182, 2012. (* equal contributions) (final pdf on publisher pages)

  10. Samuel Kaski and Jaakko Peltonen. Dimensionality Reduction for Data Visualization. IEEE Signal Processing Magazine, 28(2):100-104, 2011. (preprint pdf, final pdf on publisher pages)

  11. Joni Pajarinen, Jaakko Peltonen, and Mikko A. Uusitalo. Fault tolerant machine learning for nanoscale cognitive radio. Neurocomputing, 74(5):753-764, 2011. (preprint pdf, final version on publisher pages)

  12. Mikko A. Uusitalo, Jaakko Peltonen, and Tapani Ryhänen. Machine Learning: How It Can Help Nanocomputing. Journal of Computational and Theoretical Nanoscience, 8:1347-1363, 2011. (final pdf on publisher pages)

  13. 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. (abstract, preprint pdf, final pdf at JMLR)

  14. Jaakko Peltonen, Yusuf Yaslan, and Samuel Kaski. Relevant subtask learning by constrained mixture models. Intelligent Data Analysis, 14:641-662, 2010. (abstract, preprint pdf, final version on publisher pages)

  15. 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. (abstract, preprint pdf, final version on publisher pages) © Elsevier B. V.

  16. 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. (html)

  17. Jaakko Peltonen and Samuel Kaski. Discriminative Components of Data. IEEE Transactions on Neural Networks, 16:68-83, 2005. (preprint abstract, preprint pdf, final paper on IEEE pages)

  18. Jaakko Peltonen, Arto Klami, and Samuel Kaski. Improved Learning of Riemannian Metrics for Exploratory Data Analysis. Neural Networks, vol. 17, pages 1087-1100, 2004. (preprint abstract, preprint gzipped postscript, preprint pdf, final paper on Elsevier pages, erratum to final paper on Elsevier pages)

  19. 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 abstract, preprint gzipped postscript, preprint pdf, final paper on IEEE pages)

Refereed International Conference Publications


  1. Md Hijbul Alam*, Jaakko Peltonen*, Jyrki Nummenmaa, and Kalervo Järvelin. Author Tree-structured Hierarchical Dirichlet Process. In Proceedings of DS 2018, the 21st Internatioal Conference on Discovery Science, accepted for publication, 2018. (* equal contributions)

  2. Elizaveta Zimina, Jyrki Nummenmaa, Kalervo Järvelin, Jaakko Peltonen, Kostas Stefanidis and Heikki Hyyrö. GQA: Grammatical Question Answering for RDF Data. In Proceedings of ESWC 2018, Extended Semantic Web Conference, accepted for publication, 2018.

  3. Md Hijbul Alam*, Jaakko Peltonen*, Jyrki Nummenmaa, and Kalervo Järvelin. Tree-structured Hierarchical Dirichlet Process. (* equal contributions) In Proceedings of DCAI 2018, 15th International Conference on Distributed Computing and Artificial Intelligence, accepted for publication, 2018.

  4. Jaakko Peltonen, Ziyuan Lin, Kalervo Järvelin, and Jyrki Nummenmaa. PIHVI: Online Forum Posting Analysis with Interactive Hierarchical Visualization. In Proceedings of ESIDA 2018, 2nd ACM IUI Workshop on Exploratory Search and Interactive Data Analytics, CEUR-WS, 2018. (final paper on publisher pages)

  5. Stevan Rudinac, Tat-Seng Chua, Nicolas Diaz-Ferreyra, Gerald Friedland, Tatjana Gornostaja, Benoit Huet, Rianne Kaptein, Krister Linén, Marie-Francine Moens, Jaakko Peltonen, Miriam Redi, Markus Schedl, David A. Shamma, Alan Smeaton, and Lexing Xie. Rethinking Summarization and Storytelling for Modern Social Multimedia. In Proceedings of MMM'18, The 24th International Conference on Multimedia Modeling, pages 632-644, Springer, 2018. (preprint pdf, final paper on publisher pages)

  6. Kumaripaba Athukorala, Luana Micallef, Chao An, Aki Reijonen, Jaakko Peltonen, Tuukka Ruotsalo, and Giulio Jacucci. Visualizing activity traces to support collaborative literature searching. In Proceedings of VINCI '17, the 10th International Symposium on Visual Information Communication and Interaction, pages 45-52, ACM, 2017. (final article on publisher webpages)

  7. Ziyuan Lin and Jaakko Peltonen. An Information Retrieval Approach for Finding Dependent Subspaces of Multiple Views. In Proceedings of MLDM 2017, International Conference on Machine Learning and Data Mining, pages 1-16, Springer, 2017. (preprint pdf, final article on publisher webpages)

  8. Jaakko Peltonen, Kseniia Belorustceva, and Tuukka Ruotsalo. Improving Search Result Comprehension by Topic-Relevance Map Visualization. Refereed extended abstract (4 pages), in Proceedings of IUI 2017, 22nd ACM International Conference on Intelligent User Interfaces, 2017. (final article on publisher webpages)

  9. Jaakko Peltonen, Jonathan Strahl, and Patrik Floreen. Negative Relevance Feedback for Exploratory Search with Visual Interactive Intent Modeling. In Proceedings of IUI 2017, 22nd ACM International Conference on Intelligent User Interfaces, 2017. (final open access article on publisher webpages)

  10. Jaakko Peltonen, Kseniia Belorustceva, and Tuukka Ruotsalo. Topic-Relevance Map: Visualization for Improving Search Result Comprehension. In Proceedings of IUI 2017, 22nd ACM International Conference on Intelligent User Interfaces, 2017. (final open access article on publisher webpages)

  11. Jaakko Peltonen and Ziyuan Lin. Parallel Coordinate Plots for Neighbor Retrieval. In Proceedings of IVAPP 2017, International Conference on Information Visualization Theory and Applications, 2017. (final article on publisher webpages)

  12. Hamed R. Tavakoli, Hanieh Poostchi, Jaakko Peltonen, Jorma Laaksonen, and Samuel Kaski. Preliminary studies on personalized preference prediction from gaze in comparing visualizations. In Proceedings of ISVC'16, 12th International Symposium on Visual Computing, part II, pages 576-585, Springer, 2016. (final article on publisher webpages)

  13. Mats Sjöberg, Hung-Han Chen, Patrik Floréen, Markus Koskela, Kai Kuikkaniemi, Tuukka Lehtiniemi, and Jaakko Peltonen. Digital Me: Controlling and Making Sense of My Digital Footprint. In Proceedings of Symbiotic 2016, The 5th International Workshop on Symbiotic Interaction, pages 155-167, Springer, 2017. (preprint pdf, final open access article on publisher webpages)

  14. Jaakko Peltonen and Ziyuan Lin. Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off. In Proceedings of GD 2016, The 24th International Symposium on Graph Drawing & Network Visualization, pages 52-64, Springer, 2016. (final article on publisher webpages)

  15. Chirayu Wongchokprasitti, Jaakko Peltonen, Tuukka Ruotsalo, Payel Bandyopadhyay, Giulio Jacucci and Peter Brusilovsky. User Model In a Box: Cross-System User Model Transfer for Resolving Cold Start Problems. In Proceedings of UMAP'15, The 23rd Conference on User Modelling, Adaptation and Personalization, pages 289-301, Springer, 2015. (final paper on publisher pages, slides, presentation in UMAP conference navigator)

  16. Zhirong Yang, Jaakko Peltonen, and Samuel Kaski. Majorization-Minimization for Manifold Embedding. In Proceedings of AISTATS'15, The 18th International Conference on Artificial Intellgence and Statistics, JMLR W&CP, pp. 1088-1097, 2015. (abstract on publisher webpages, paper on publisher webpages, supplementary information on publisher webpages)

  17. Salvatore Andolina, Khalil Klouche, Jaakko Peltonen, Mohammad Hoque, Tuukka Ruotsalo, Diogo Cabral, Arto Klami, Dorota Glowacka, Patrik Floreen, and Giulio Jacucci. IntentStreams: Smart Parallel Search Streams for Branching Exploratory Search. In Proceedings of ACM IUI 2015, The 20th ACM Conference on Intelligent User Interfaces, pp. 300-305, 2015. (final paper on publisher pages, YouTube video of the system)

  18. Zhirong Yang, Jaakko Peltonen, and Samuel Kaski. Optimization Equivalence of Divergences Improves Neighbor Embedding. In Proceedings of ICML 2014, The 31st International Conference on Machine Learning, JMLR W&CP 32:460-468, 2014. (final pdf on publisher pages, supplemental document, code)

  19. Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen and Samuel Kaski. Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. In Proceedings of AAAI-14, The Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014. (preprint pdf, final pdf on publisher pages)

  20. Jaakko Peltonen and Ziyuan Lin. Information Retrieval Perspective to Meta-visualization. In Cheng Soon Ong and Tu Bao Ho, editors, Proceedings of ACML 2013, Fifth Asian Conference on Machine Learning, JMLR W&CP 29:165-180, 2013. (final pdf on publisher pages)

  21. Tuukka Ruotsalo*, Jaakko Peltonen*, Manuel Eugster*, Dorota Glowacka, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. Directing Exploratory Search with Interactive Intent Modeling. In Proceedings of CIKM 2013, ACM Conference on Information and Knowledge Management, pages 1759-1764. ACM, 2013. (* equal contributions) (preprint pdf, final pdf on publisher pages)

  22. Jaakko Peltonen and Ziyuan Lin. Multiplicative Update For Fast Optimization Of Information Retrieval Based Neighbor Embedding. In Saeid Sanei, Paris Smaragdis, Asoke Nandi, Anthony TS Ho, and Jan Larsen, editors, Proceedings of MLSP 2013, IEEE International Workshop on Machine Learning for Signal Processing, IEEE, 2013. (final pdf on publisher pages)

  23. Joni Pajarinen and Jaakko Peltonen. Expectation maximization for average reward decentralized POMDPs. In Proceedings of ECML PKDD 2013, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pages 129-144. Springer, 2013. (final paper on publisher pages)

  24. Jaakko Peltonen, Max Sandholm, and Samuel Kaski. Information Retrieval Perspective to Interactive Data Visualization. In Proceedings of Eurovis 2013, the Eurographics Conference on Visualization - short papers, pages 49-53. European Association for Computer Graphics, 2013. (preprint pdf, final paper on publisher pages)

  25. Zhirong Yang, Jaakko Peltonen, and Samuel Kaski. Scalable Optimization of Neighbor Embedding for Visualization. In Proceedings of ICML 2013, International Conference on Machine Learning, JMLR W&CP 28(2):127-135, 2013. (final pdf on publisher pages)

  26. Jaakko Peltonen and Konstantinos Georgatzis. Efficient Optimization for Data Visualization as an Information Retrieval Task. In Ignacio Santamaria, 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. IEEE, 2012. (preprint pdf, final paper on IEEE pages)

  27. Ali Faisal*, Jussi Gillberg*, Jaakko Peltonen*, Gayle Leen, and Samuel Kaski. Sparse Nonparametric Topic Model for Transfer Learning. In Proceedings of ESANN 2012, 20th European Symposium on Artificial Neural Networks, ESANN, 2012. (* equal contributions) (preprint pdf, final pdf on publisher pages)

  28. Joni Pajarinen and Jaakko Peltonen. Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning. In J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F. C. N. Pereira, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 24 (Proceedings of NIPS 2011), pages 2636-2644, 2011. (PDF on publisher pages)

  29. Gayle Leen, Jaakko Peltonen, and Samuel Kaski. Focused Multi-task Learning Using Gaussian Processes. In Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, and Michalis Vazirgiannis, editors, Machine Learning and Knowledge Discovery in Databases (proceedings of ECML PKDD 2011), Part II, pages 310-325. Springer-Verlag, Berlin Heidelberg, 2011. Winner of the ECML PKDD 2011 Best Paper Award in Machine Learning. (preprint PDF, final PDF on publisher pages)

  30. Joni Pajarinen and Jaakko Peltonen. Efficient planning for factored infinite-horizon DEC-POMDPs. In Proceedings of IJCAI-11, the 22nd International Joint Conference on Artificial Intelligence, pages 325-331. AAAI Press, 2011. (abstract, final PDF on publisher pages)

  31. Jaakko Peltonen and Samuel Kaski. Generative Modeling for Maximizing Precision and Recall in Information Visualization. In Geoffrey Gordon, David Dunson, and Miroslav Dudik, eds., Proceedings of AISTATS 2011, the 14th International Conference on Artificial Intelligence and Statistics. JMLR W&CP, vol. 15, pages 579-587, 2011. (abstract, final pdf on publisher pages, supplementary information)

  32. Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, and Mikko A. Uusitalo. Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations. In Proceedings of ECML PKDD 2010, part III, pages 1-16. Springer-Verlag, Berlin Heidelberg, 2010. (preprint pdf, final version on publisher pages)

  33. 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. ACM, New York, NY, USA, 2010. (preprint pdf, final version on publisher pages)

  34. 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, pages 2178-2181. IEEE, 2010. (abstract, preprint pdf, final version on publisher pages)

  35. 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. (preprint pdf, final version on publisher pages. Note: work was also supported by Academy of Finland decision 123983.)

  36. 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. Springer, Berlin Heidelberg, 2009. (abstract, preprint pdf, final paper on Springer pages) © Springer-Verlag Berlin Heidelberg 2009

  37. Jaakko Peltonen, Helena Aidos, and Samuel Kaski. Supervised Nonlinear Dimensionality Reduction by Neighbor Retrieval. In Proceedings of the IEEE 2009 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), pages 1809-1812. IEEE, 2009. (abstract, preprint pdf, final paper on publisher pages)

  38. Jaakko Peltonen, Mikko A. Uusitalo, and Joni Pajarinen. Nano-scale Fault Tolerant Machine Learning for Cognitive Radio. In proceedings of the 2008 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2008), pages 163-168. IEEE, 2008. (final paper on IEEE pages)

  39. Samuel Kaski and Jaakko Peltonen. Learning from Relevant Tasks Only. In Joost N. Kok, Jacek Koronacki, Ramon Lopez de Mantaras, Stan Matwin, Dunja Mladenic, and Andrzej Skowron, editors, Machine Learning: ECML 2007 (Proceedings of the 18th European Conference on Machine Learning), Lecture Notes in Artificial Intelligence 4701, pages 608-615. Springer-Verlag, Berlin, Germany, 2007. (abstract, preprint pdf, final paper on Springer pages) © 2007 Springer-Verlag.

  40. Jaakko Peltonen, Jacob Goldberger, and Samuel Kaski. Fast Semi-supervised Discriminative Component Analysis. In Konstantinos Diamantaras, T?ay Adali, Ioannis Pitas, Jan Larsen, Theophilos Papadimitriou, and Scott Douglas, editors, Machine Learning for Signal Processing XVII, pages 312-317. IEEE, 2007. (abstract, preprint pdf, final paper on publisher pages)

  41. Merja Oja, Jaakko Peltonen, and Samuel Kaski. Estimation of human endogenous retroviruses from sequence databases. In Juho Rousu, Samuel Kaski, and Esko Ukkonen, editors, Probabilistic Modeling and Machine Learning in Structural and Systems Biology (PMSB 2006), workshop proceedings, pages 50-54, Helsinki University Printing House, 2006. (abstract, gzipped postscript, pdf)

  42. Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski. Sequential Information Bottleneck for Finite Data. In Russ Greiner and Dale Schuurmans, editors, Proceedings of the Twenty-First International Conference on Machine Learning (ICML 2004), pp. 647-654, Omnipress, Madison, WI, 2004. (abstract, pdf, final paper on publisher pages)

  43. Jaakko Peltonen, Arto Klami, and Samuel Kaski. Learning Metrics for Information Visualization. In Proceedings of the Workshop on Self-Organizing Maps (WSOM'03), Hibikino, Kitakyushu, Japan, September 2003. pp. 213-218. (abstract, postscript, gzipped postscript, pdf)

  44. Samuel Kaski and Jaakko Peltonen. Informative discriminant analysis. In: Tom Fawcett and Nina Mishra, editors, Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), pp. 329-336, AAAI Press, Menlo Park, CA, 2003. (abstract, gzipped postscript, pdf)

  45. Jarkko Venna, Samuel Kaski, and Jaakko Peltonen. Visualizations for Assessing Convergence and Mixing of MCMC. N. Lavrac, D. Gamberger, H. Blockeel, L. Todorovski, editors, Proceedings of the 14th European Conference on Machine Learning (ECML 2003), pp. 432-443. Springer, Berlin, 2003. (abstract, postscript, gzipped postscript, pdf)

  46. Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski. Discriminative clustering of text documents. In: Lipo Wang, Jagath C. Rajapakse, Kunihiko Fukushima, Soo-Young Lee, Xin Yao (eds.) Proceedings of ICONIP'02, 9th International Conference on Neural Information Processing, volume 4, pages 1956-1960. IEEE, Piscataway, NJ, 2002. (abstract, postscript, gzipped postscript, pdf)

  47. Jaakko Peltonen, Arto Klami, and Samuel Kaski. Learning More Accurate Metrics for Self-Organizing Maps. In Jos?R. Dorronsoro, editor, Artificial Neural Networks - ICANN 2002, International Conference, Madrid, Spain, August 2002, Proceedings, pp. 999-1004. Springer, 2002. (abstract, postscript, gzipped postscript, pdf) © Springer-Verlag

  48. 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. IEEE, Piscataway, NJ, 2001. (abstract, postscript, gzipped postscript, pdf)

  49. Samuel Kaski, Janne Sinkkonen, and Jaakko Peltonen. Data visualization and analysis with self-organizing maps in learning metrics. In Y. Kambayashi, W. Winiwarter, M. Arikawa, eds., Proceedings of DaWak'01, Third International Conference on Data Warehousing and Knowledge Discovery, pages 162-173. Springer, Berlin, 2001. (pdf at Springer pages)

Refereed Finnish Conference Publications


  1. 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, pages 41-49. Finnish Artificial Intelligence Society, 2002.

Publications as Editor


  1. Jaakko Peltonen, Tapani Raiko, and Samuel Kaski (editors). Machine learning for signal processing 2010, Neurocomputing vol. 80, 2012. (volume on publisher pages)

Other Scientific Publications


  1. Ziyuan Lin* and Jaakko Peltonen*. An Information Retrieval Approach to Finding Dependent Subspaces of Multiple Views. ArXiv preprint, arXiv:1511.06423 [stat], 2015. (* equal contributions)

  2. Antti Honkela, Jaakko Peltonen, Hande Topa, Iryna Charapitsa, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil Lawrence and Magnus Rattray. Genome-wide modelling of transcription kinetics reveals patterns of RNA production delays. In NIPS 2015 Workshop on Machine Learning in Computational Biology, 2015.

  3. Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, and Samuel Kaski. SciNet: Interactive intent modeling for information discovery. In Proceedings of SIGIR'15, the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1043-1044. ACM, New York, NY, 2015. Refereed abstract (2 pages). (PDF)

  4. Antti Honkela, Jaakko Peltonen, Hande Topa, Iryna Charapitsa, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil D. Lawrence, and Magnus Rattray. Genome-wide modelling of transcription kinetics reveals patterns of RNA processing delays. ArXiv preprint, arXiv:1503.01081 [q-bio.GN], 2015.

  5. Jaakko Peltonen, Ali Faisal, Elisabeth Georgii, Johan Rung and Samuel Kaski. Toward computational cumulative biology by combining models of biological datasets. In NIPS 2014 Workshop on Machine Learning in Computational Biology, 2014.

  6. Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymaki, Giulio Jacucci, Samuel Kaski. Bayesian Optimization in Interactive Scientific Search. In NIPS 2014 Workshop on Bayesian Optimization in Academia and Industry, 2014.

  7. Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen and Samuel Kaski. Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. In Proceedings of RCRA 2014, 21st RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, 2014.

  8. Antti Kangasrääsiö, Dorota Glowacka, Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. Interactive Visualization of Search Intent for Exploratory Information Retrieval. In ICML 2014 Workshop on Crowdsourcing and Human Computing, 2014.

  9. Ali Faisal, Jaakko Peltonen, Elisabeth Georgii, Johan Rung, and Samuel Kaski. Toward computational cumulative biology by combining models of biological datasets. ArXiv preprint, arXiv:1404.0329v1 [q-bio.QM], 2014.

  10. Tuukka Ruotsalo, Jaakko Peltonen, Aki Reijonen, Giulio Jacucci, Manuel J.A. Euster, and Samuel Kaski. IntentRadar: Interactive Search User Interface that Anticipates User's Search Intents. Refereed extended abstract (4 pages) in CHI Interactivity 2014, 2014.

  11. Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Giulio Jacucci, Aki Reijonen and Samuel Kaski. Lost in Publications? How to Find Your Way in 50 Million Scientific Documents. Refereed extended abstract (5 pages) in the NIPS 2013 workshop on Big Learning: Advances in Algorithms and Data Management, 2013. (pdf extended abstract)

  12. Jaakko Peltonen. Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization. Abstract in Daniel E. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, and Stefan Wrobel, editors, Information Visualization, Visual Data Mining and Machine Learning, Dagstuhl Reports, 2(2): 58-83, 2012. (Online report)

  13. Jaakko Peltonen and Samuel Kaski. Generative modeling for maximizing precision and recall in information visualization. Technical Report TKK-ICS-R38, Aalto University School of Science and Technology, Department of Information and Computer Science, Espoo, Finland, November 2010.

  14. Jaakko Peltonen, Yusuf Yaslan, and Samuel Kaski. Variational Bayes Learning from Relevant Tasks Only. Refereed extended abstract (4 pages), in the NIPS 2008 Learning from Multiple Sources Workshop. (abstract, pdf extended abstract)

  15. 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.

  16. Mikko A. Uusitalo and Jaakko Peltonen. Nanocomputing with machine learning. Poster in Nanotech Northern Europe 2008 (NTNE 2008), 2008.

  17. Merja Oja, Jaakko Peltonen, Jonas Blomberg and Samuel Kaski. Estimating human endogeneous retrovirus activities in various tissues with a hidden Markov mixture model. Poster in Intelligent Systems for Molecular Biology & European Conference on Computational Biology 2007 (ISMB/ECCB 2007), Vienna, Austria, July 21-25, 2007.

  18. Samuel Kaski and Jaakko Peltonen. Learning from Relevant Tasks Only. Technical Report E11, Helsinki University of Technology, Publications in Computer and Information Science, May 2007. (pdf)

  19. Jaakko Peltonen and Samuel Kaski. Learning when only some of the training data are from the same distribution as test data. Poster in the NIPS 2006 workshop on Learning when test and training inputs have different distributions, December 9, Whistler, Canada. (abstract, pdf extended abstract, pdf poster in A0 size)

  20. Jaakko Peltonen, Jacob Goldberger, and Samuel Kaski. Fast Discriminative Component Analysis for Comparing Examples. Refereed extended abstract (5 pages). In NIPS 2006 workshop on Learning to Compare Examples. (abstract, pdf)

  21. Merja Oja, Jaakko Peltonen, and Samuel Kaski. A hidden Markov model for estimating human endogenous retrovirus activities from expressed sequence databases. Poster in the European Conference on Computational Biology (ECCB 2006), Eilat, Israel, January 21-24, 2007. (abstract)

  22. 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, December 2003.

Theses


  1. Jaakko Peltonen. Data Exploration with Learning Metrics. D.Sc. thesis. 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.

  2. 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.

Popular-science publications


  1. Jaakko Peltonen. Itseorganisoituvat kartat oppivissa metriikoissa. Tekniikan Akateemiset 5/2002. (pdf at publisher pages)

Recent Research Talks

This is a partial list of recent research talks I have given.

Some Useful Resources

PASCAL2 network, Google Scholar, IEEE Xplore, Lecture Notes in Computer Science (Springer), NIPS proceedings, KDnuggets, mldata.org data set repository.