Jaakko Peltonen Jaakko Peltonen

I am a professor of statistics (data analysis) at Tampere University, Faculty of Information Technology and Communication Sciences, unit of Computing Sciences and the data science team within the unit.

I am the leader of the Statistical Machine Learning and Exploratory Data Analysis (SMiLE) research group and a member of the Academy of Finland Centre of Excellence in Game Culture Studies.

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

I 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.

New: open positions for doctoral researchers in 3-year doctoral program pilot of the Finnish Doctoral Program Network in Artificial Intelligence. Choose Jaakko Peltonen as your supervisor. Apply now! Deadline to apply: April 2, 2024.

Contact information

Room:Hervanta campus, Tietotalo, room TF316B
E-Mail:firstname dot lastname at tuni dot fi
Phone:+358 50 3623628
Twitter:@JaakkoTPeltonen
ORCID:
Google Scholar:profile
DBLP:profile

Positions of Trust and Expertise

I am an editor-in-chief of Scandinavian Journal of Statistics, associate editor of Transactions on Machine Learning Research, associate editor of Neural Processing Letters, associate editor of Frontiers in Artificial Intelligence, and editorial board member of Heliyon (curr. advisory editorial board member). I have been an editorial board member of Neural Networks, and earlier co-edited a special issue of Neurocomputing on machine learning for signal processing. I am a member of the executive committee of the European Neural Network Society. I have been a program committee member for 111 conferences/workshops, including NeurIPS 2017-2023, ICML 2016-2020 and 2023, UAI 2023, ECMLPKDD 2016-2023, IJCAI 2019-2023, Eurovis 2019-2021 and 2024, IEEE Vis 2021-2023, AAAI 2018-2024, IUI 2022-2024, AISTATS 2017-2024, ICANN 2011-2014 and 2016-2021, ICLR 2019-2022 and 2024, ESANN 2014-2023, and several other series including ACML, CIKM, MLSP, WSOM, DaWaK, ISVC, IEEE VAST, NC2 and others. I am a founder of the MLVis workshop series (now 9 years running), and 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 over 111 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

I am one of the two responsible professors for two master's degree study tracks in the Master's Degree Programme in Computing Sciences at Tampere University: and also for the master's programme that preceded them, the International Master's Degree Programme on Computational Big Data Analytics (CBDA). See the pages of the Data Science and Statistical Data Analytics tracks for how to apply. The next application round will be around December 2024 - January 2025. See also a YouTube video webinar about the Computing Sciences programme which includes the Data Science and Statistical Data Analytics tracks.

In spring 2024 I lecture the courses DATA.STAT.760 Learning from Multiple Sources, and DATA.810 Master's Thesis Seminar, Data Science & Statistical Data Analytics at Tampere University.

Earlier teaching:
I have lectured several implementations at Tampere University (and previously University of Tampere) of the courses DATA.STAT.840 Statistical Methods for Text Data Analysis, DATA.STAT.760 Learning from Multiple Sources, MTTTS16 Learning from Multiple Sources, DATA.STAT.770 Dimensionality Reduction and Visualization, MTTTS17 Dimensionality Reduction and Visualization, DATA.STAT.510 Mathematical and Statistical Software, MTTTA11 Statistical Software, Python, MTTS1 Statistical Analysis with Missing Data (Advanced), MATH.APP.450 Basic Course on Mathematical Modelling, DATA.810 Master's Thesis Seminar, Data Science & Statistical Data Analytics, MTTTS11 Master's Seminar and Thesis, MTTTS2 Pro gradu thesis and seminar, YKYYHT2 Yhteiskunnan mittaaminen. Earlier I have lectured implementations of the courses T-61.2020 From Data to Knowledge Project Assignment, T-61.6040 Advanced Course in Information Visualization T-61.5010 Information Visualization, T-61.3050 Machine Learning: Basic Principles, T-61.6040 Multi-view and Multi-task Learning, T-61.3040 Statistical Modeling of Signals, T-61.6040 Learning from Multiple Sources at Aalto University, and 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

  • Mykola Andrushchenko, doctoral student, Tampere University1
  • S. F. Ebrahimi, doctoral student, Tampere University
  • Joonas Kauppinen, doctoral student, Tampere University1
  • Sini Knuutila, doctoral student, Tampere University (co-supervised)
  • Ziyuan Lin, doctoral student, Aalto University and Tampere University
  • Hanieh Poostchi, doctoral student, Aalto University1
  • Terhi Savonen, doctoral student, Tampere University (co-supervised)
  • Jonathan Strahl, doctoral student, Aalto University1
  • Wen Xu, doctoral student, Tampere University1
  • Elizaveta Zimina, doctoral student, University of Tampere1
1co-supervised

New: open positions for doctoral researchers in 3-year doctoral program pilot of the Finnish Doctoral Program Network in Artificial Intelligence. Choose Jaakko Peltonen as your supervisor. Apply now! Deadline to apply: April 2, 2024.

Alumni:
  • Chien Lu, doctoral student, Tampere University, received DSc degree Sep 2023
  • Olli Kuparinen, doctoral student, Tampere University1, received doctoral degree Jun 2021, now postdoctoral researcher at Tampere University
  • Apurva Nandan, master's student, master's student, Tampere University, received MSc degree Jun 2018, now at CSC - IT Center for Science
  • Zhe Xie, master's student, Aalto University, received MSc degree Mar 2015
  • Ali Faisal, received DSc degree Aug 2014, later postdoc at Aalto University, now at Coca-Cola European Partners
  • Joni Pajarinen, received DSc degree Feb 2013, later postdoc at Aalto University and TU Darmstadt, now assistant professor at Tampere University
  • Jussi Gillberg, received MSc degree 2011, now doctoral student at Aalto University
  • Max Sandholm, received MSc degree 2013
  • Essi Peltonen (prev. Syrjälä), received PhD degree 2023, now at Oriola.
  • Konstantinos Georgatzis, doctoral student, later at University of Edinburgh, now at QuantumBlack
  • Jaakko Viinikanoja, doctoral student
  • Helena Aidos, doctoral student, later at Instituto de Telecomunicacoes, Portugal, now at Universidade de Lisboa
  • Markus Losoi, undergraduate student

Publications

Journal Publications

  1. Elizaveta Zimina, Kalervo Järvelin, Jaakko Peltonen, Aarne Ranta, Kostas Stefanidis, and Jyrki Nummenmaa. Linguistic Summarisation of Multiple Entities in RDF Graphs. Applied Computing and Intelligence, 4(1):1-18, 2024. (final article on publisher webpages)

  2. Mari Hatavara, Kirsi Sandberg, Mykola Andrushchenko, Sari Hälikkö, Jyrki Nummenmaa, Timo Nummenmaa, Jaakko Peltonen, and Matti Hyvärinen. Computational recognition of narratives: Applying narratological definitions to the analysis of political language use. Narrative Inquiry, Online First, 2024. (final article on publisher webpages)

  3. Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki, and Antti Roine. Forecasting emergency department occupancy with advanced machine learning models and multivariable input. International Journal of Forecasting, 40(4):1410-1420, 2024. (final article on publisher webpages)

  4. Matti Hyvärinen, Jussi Kurunmäki, Risto Turunen, Kari Teräs, Mykola Andrushchenko, and Jaakko Peltonen. 'Democracy' and 'People's Power' in the Finnish Parliament - the Struggle between Representative, Participatory and Direct Democracy. Redescriptions: Political Thought, Conceptual History and Feminist Theory, 26 (2): 117-140, 2023. (final article on publisher webpages)

  5. Essi J. Peltonen, Riitta Veijola, Jorma Ilonen, Mikael Knip, Harri Niinikoski, Jorma Toppari, Helena E. Virtanen, Suvi M. Virtanen, Jaakko Peltonen, and Jaakko Nevalainen. What is the role of puberty in the development of islet autoimmunity and progression to type 1 diabetes? European Journal of Epidemiology, 38:689-697, 2023. (final open access article on publisher webpages)

  6. Markus Wallinger, Daniel Archambault, David Auber, Martin N&oeml;llenburg, and Jaakko Peltonen. Faster Edge-Path Bundling Through Graph Spanners. Computer Graphics Forum, Early View, 2023. (final article on publisher webpages)

  7. Stef van den Elzen, Gennady Andrienko, Natalia Andrienko, Brian D. Fisher, Rafael M. Martins, Jaakko Peltonen, Alexandry C. Telea, and Michel Verleysen. The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications. IEEE Computer Graphics and Applications, 43:78-88, 2023. (final article on publisher webpages)

  8. Sangita Kulathinal, Jaakko Peltonen, and Mikko J. Sillanpää. Professor Elja Arjas: A prominent figure in establishing statistics in Finland. Scandinavian Journal of Statistics, 50(1):1-2, 2023. (final article on publisher webpages)

  9. Jalmari Tuominen, Francesco Lomio, Niku Oksala, Ari Palomäki, Jaakko Peltonen, Heikki Huttunen, and Antti Roine. Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach. BMC Medical Informatics and Decision Making, 22, article 134, 2022. (final open access article on publisher webpages)

  10. Soeren Nickel, Max Sondag, Wouter Meulemans, Stephen G. Kobourov, Jaakko Peltonen, and Martin Nollenburg. Multicriteria Optimization for Dynamic Demers Cartograms. IEEE Transactions on Visualization and Computer Graphics, 28(6):2376-2387, 2022. (final article on publisher webpages)

  11. Essi Syrjälä, Harri Niinikoski, Helena E. Virtanen, Jorma Ilonen, Mikael Knip, Nina Hutri-Kähönen, Katja Pahkala, Olli T. Raitakari, Wiwat Rodprasert, Jorma Toppari, Suvi M. Virtanen, Riitta Veijola, Jaakko Peltonen, and Jaakko Nevalainen. Determining the timing of pubertal onset via a multicohort analysis of growth. PLOS ONE, 16(11):e0260137, 2021. (final open access article on publisher webpages)

  12. Sini Knuutila, Olli Kuparinen, Liisa Mustanoja, Unni Leino, Jenni Santaharju, and Jaakko Peltonen. Miksi d katoaa? Katomuotojen diffuusion etenemisen syistä Helsingin puhekielessä yleiskielen hd-yhtymässä. Sananjalka, accepted for publication, 2022.

  13. Olli Kuparinen, Jenni Santaharju, Unni Leino, Liisa Mustanoja, and Jaakko Peltonen. Katomuotojen eteneminen yleiskielen hd-yhtymässä Helsingin puhekielessä. Virittäjä, 126(3):316-338, 2023. (final article on publisher webpages)

  14. Emma Beauxis-Aussalet, Michael Behrisch, Rita Borgo, Duen Horng Chau, Christopher Collins, David Ebert, Mennatallah El-Assady, Alex Endert, Daniel A. Keim, Jörn Kohlhammer, Daniela Oelke, Jaakko Peltonen, Maria Riveiro, Tobias Schreck, Hendrik Strobelt, and Jarke J. van Wijk. The Role of Interactive Visualization in Fostering Trust in AI. IEEE Computer Graphics and Applications, 41(6):7-12, 2021. (final article on publisher webpages)

  15. Markus Wallinger, Daniel Archambault, David Auber, Martin Nöllenburg, and Jaakko Peltonen. Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach. IEEE Transactions on Visualization and Computer Graphics (proceedings of IEEE VIS 2021), 28(1):313-323, 2021. (final article on publisher webpages)

  16. Mykola Andrushchenko, Kirsi Sandberg, Risto Turunen, Jani Marjanen, Mari Hatavara, Jussi Kurunmäki, Timo Nummenmaa, Matti Hyvärinen, Kari Teräs, Jaakko Peltonen, and Jyrki Nummenmaa. Using parsed and annotated corpora to analyze parliamentarians' talk in Finland. Journal of the Association for Information Science and Technology (JASIST), 73(2):288-302, 2021. (final open access article on publisher webpages)

  17. Abel Szkalisity, Filippo Piccinini, Attila Beleon, Tamas Balassa, Istvan Gergely Varga, Ede Migh, Csaba Molnar, Lassi Paavolainen, Sanna Timonen, Indranil Banerjee, Elina Ikonen, Yohei Yamauchi, Istvan Ando, Jaakko Peltonen, Vilja Pietiäinen, Viktor Honti, and Peter Horvath. Regression plane concept for analysing continuous cellular processes with machine learning. Nature Communications, 12, 2532, 2021. (final open access article on publisher webpages)

  18. Olli Kuparinen, Jaakko Peltonen, Liisa Mustanoja, Unni Leino, and Jenni Santaharju. Lects in Helsinki Finnish - a probabilistic component modeling approach. Language Variation and Change, First View, pages 1-26, 2021. (preprint pdf, final paper on publisher webpages)

  19. Katariina Koivusaari, Essi Syrjälä, Sari Niinistö, Hanna-Mari Takkinen, Suvi Ahonen, Mari Âkerlund, Tuuli E. Korhonen, Jorma Toppari, Jorma Ilonen, Jaakko Peltonen, Jaakko Nevalainen, Mikael Knip, Tapani Alatossava, Riitta Veijola, and Suvi M. Virtanen. Consumption of differently processed milk products in infancy and early childhood and the risk of islet autoimmunity. British Journal of Nutrition, February 2020, pages 1-17, 2020. (final open access pdf, final article on publisher webpages)

  20. Mika Vanhala, Chien Lu, Jaakko Peltonen, Sanna Sundqvist, Jyrki Nummenmaa, and Kalervo Järvelin. The Usage of Large Data Sets in Consumer Online Behaviour: A Bibliometric and Computational Text-mining-driven Analysis of Previous Research. Journal of Business Research, 106:46-59, January 2020. (accepted manuscript pdf, final article on publisher webpages)

  21. Olli Kuparinen, Liisa Mustanoja, Jaakko Peltonen, Jenni Santaharju, and Unni-Päivä Leino. Muutosmallit Helsingin puhekielessä. Sananjalka, 61(61):30-56, 2019. (preprint pdf, final article on publisher webpages)

  22. Essi Syrjälä, Jaakko Nevalainen, Jaakko Peltonen, Hanna-Mari Takkinen, Leena Hakola, Mari Âkerlund, Riitta Veijola, Jorma Ilonen, Jorma Toppari, Mikael Knip, and Suvi M. Virtanen. A Joint Modeling Approach for Childhood Meat, Fish and Egg Consumption and the Risk of Advanced Islet Autoimmunity. Scientific Reports, 9, Article number 7760, 2019. (final open access article on publisher webpages)

  23. 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)

  24. 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)

  25. 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. (preprint pdf, final article on publisher webpages)

  26. 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)

  27. 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)

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

  29. 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. (preprint pdf, final pdf on publisher pages)

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

  31. 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)

  32. 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)

  33. 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)

  34. 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)

  35. 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)

  36. 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)

  37. 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.

  38. 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)

  39. 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)

  40. 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)

  41. 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. Elizaveta Zimina, Kalervo Järvelin, Jaakko Peltonen, Aarne Ranta, Jyrki Nummenmaa. TraQuLA: Transparent Question Answering Over RDF Through Linguistic Analysis. In Proceedings of ICWE 2024, 24th International Conference on Web Engineering, 2024.

  2. Jaakko Peltonen, Wen Xu, Timo Nummenmaa, and Jyrki Nummenmaa. Fair Neighbor Embedding. In Proceedings of ICML 2023, International Conference on Machine Learning, PMLR 202:27564-27584, 2023. (final open access article on publisher webpages)

  3. Chien Lu and Jaakko Peltonen. Blooming Engagement in Flower: Computational Analysis of Player Experience on Steam. In Proceedings of ISAGA 2023, the 54th Conference of the International Simulation and Gaming Association. Simulation and Gaming for Social and Environmental Transitions, pages 340-354, 2023.
  4. Chien Lu, Giacomo Lauritano, Timo Nummenmaa and Jaakko Peltonen. Human-Environment Relationships in Alba: A Typological Analysis of Player Engagement in Steam Reviews. In DiGRA 2023 - Proceedings of the 2023 DiGRA International Conference, 2023. (final open access article on publisher webpages)

  5. Giacomo Lauritano, Valeria Marina Borodi, Chien Lu and Jaakko Peltonen. Polarized Pills vs. Gaming Thrills: Empirical Exploration of r/TheRedPill and r/TheBluePill Users in r/gaming. In DiGRA 2023 - Proceedings of the 2023 DiGRA International Conference, 2023. (final open access article on publisher webpages)

  6. Chien Lu, Diego A Mejía-Alandia and Jaakko Peltonen. Game Genres as Social Dimensions: a Computational Revisit. In Nordic DiGRA 2023, accepted for presentation, 2023.

  7. Chien Lu, Giacomo Lauritano, and Jaakko Peltonen. Cryptokitties vs. Axie Infinity: Computational Analysis of Reddit Discussions of Two NFT Games. In Proceedings of ArtsIT 2022, EAI International Conference: ArtsIT, Interactivity & Game Creation, pages 105-120, Springer, 2023. (final article on publisher pages)

  8. Kirsi Sandberg, Mykola Andrushchenko, Risto Turunen, Jani Marjanen, Jussi Kurunmäki, Jaakko Peltonen, Timo Nummenmaa, and Jyrki Nummenmaa. Analyzing Temporalities in Parliamentary Speech about Ideologies Using Dependency Parsed Data. In Proceedings of DHNB 2022, The 6th Digital Humanities in the Nordic and Baltic Countries Conference, pages 406-414, CEUR-WS, 2022. (final open access paper on publisher pages)

  9. Chien Lu and Jaakko Peltonen. Gaussian Copula Embeddings. In S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh, editors, Advances in Neural Information Processing Systems 35 (Proceedings of NeurIPS 2022, 36th Conference on Neural Information Processing Systems), pages 22078-22089, Curran Associates, Inc., 2022. (final open access paper on published webpages, final supplemental document on publisber webpages)

  10. Sorina Mustatea, Michael Aupetit, Jaakko Peltonen, Sylvain Lespinats, and Denys Dutykh. Supervised dimensionality reduction technique accounting for soft classes. In Proceedings of ESANN 2022, 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2022. (final open access article on publisher webpages)

  11. Chien Lu, Jaakko Peltonen, Timo Nummenmaa, and Jyrki Nummenmaa. Nonparametric Exponential Family Graph Embeddings for Multiple Representation Learning. In Proceedings of UAI 2022, The 38th Conference on Uncertainty in Artificial Intelligence, PMLR 180:1275-1285, PMLR, 2022. (final open access article on publisher webpages)

  12. Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa, and Kalervo Järvelin. Cross-structural Factor-topic Model: Document Analysis with Sophisticated Covariates. In Proceedings of ACML 2021, The 13th Asian Conference on Machine Learning, pages 1129-1144, PMLR, 2021. Award-winning: Best student paper award runner-up, ACML 2021. (final open access article on publisher webpages, final open access supplement on publisher webpages)

  13. Jonathan Strahl, Jaakko Peltonen, and Patrik Floreen. Directing and Combining Multiple Queries for Exploratory Search by Visual Interactive Intent Modeling. In Proceedings of INTERACT 2021, 18th IFIP TC13 International Conference on Human-Computer Interaction, pages 514-535, Springer, 2021. (final publication on publisher webpages)

  14. Chien Lu, Oğuz Buruk, Lobna Hassan, Timo Nummenmaa, and Jaakko Peltonen. "Switch" up your exercise: An empirical analysis of online user discussion of the Ring Fit Adventure exergame. In Proceedings of GamiFIN 2021, 5th International GamiFIN conference, pages 70-79, CEUR-WS, 2021. (final open access article on publisher webpages)

  15. Chien Lu, Elina Koskinen, Dale Leorke, Timo Nummenmaa, and Jaakko Peltonen. The World Is Your Playground: A Bibliometric and Text Mining Analysis of Location-Based Game Research. In Proceedings of ArtsIT 2020, 9th EAI International Conference: ArtsIT, Interactivity & Game Creation, pages 160-179, Springer, Cham., 2021. (preprint pdf, final paper on publisher webpages)

  16. Benoît Colange, Jaakko Peltonen, Michael Aupetit, Denys Dutykh, and Sylvain Lespinats. Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction. In Proceedings of NeurIPS 2020, Thirty-fourth Conference on Neural Information Processing Systems, pages 13214-13225, Curran Associates Inc., 2020. (pdf, final open access article in NeurIPS pre-proceedings)

  17. Chien Lu, Jaakko Peltonen, Jyrki Nummenmaa, and Kalervo Järvelin. Probabilistic Dynamic Non-negative Group Factor Model for Multi-source Text Mining. In Proceedings of CIKM 2020, 29th ACM International Conference on Information and Knowledge Management, pages 1035-1043, 2020. (final open access article on publisher webpages)

  18. Chien Lu, Xiaozhou Lu, Timo Nummenmaa, Zheying Zhang, and Jaakko Peltonen. Patches and Player Community Perceptions: Analysis of No Man's Sky Steam Reviews. In DiGRA 2020 - Proceedings of the 2020 DiGRA International Conference: Play Everywhere, DiGRA, 2020. (final paper on publisher webpages)

  19. Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Xiaozhou Li, and Zheying Zhang. What Makes a Trophy Hunter: An Empirical Analysis of Reddit Discussions. In Jonna Koivisto, Mila Bujií, and Juho Hamari, editors, Proceedings of GamiFIN 2020, 4th International GamiFIN conference, pages 146-156, CEUR-WS, 2020. (preprint pdf, final open access article on publisher webpages)

  20. Chien Lu and Jaakko Peltonen. Enhancing Nearest Neighbor Based Entropy Estimator for High Dimensional Distributions vis Bootstrapping Local Ellipsoid. In Proceedings of AAAI-20, Thirty-Fourth AAAI Conference on Artificial Intelligence (Proceedings of the AAAI Conference on Artificial Intelligence, volume 34 no. 4), pages 5013-5020, AAAI, 2020. (preprint pdf, final article on publisher webpages)

  21. Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, and Samuel Kaski. Scalable Probabilistic Matrix Factorization with Graph-Based Priors. In Proceedings of AAAI-20, Thirty-Fourth AAAI Conference on Artificial Intelligence, (Proceedings of the AAAI Conference on Artificial Intelligence, volume 34 no. 4), pages 5851-5858, AAAI, 2020. (preprint pdf, preprint article in ArXiv, final article on publisher webpages)

  22. Miikka Lehtonen, Chien Lu, Timo Nummenmaa, and Jaakko Peltonen. Adoption of requirements engineering methods in game development: A literature and postmortem analysis. In proceedings of ArtsIT 2019, 8th EAI International Conference: ArtsIT, Interactivity & Game Creation, pages 436-457, Springer, 2019. (preprint pdf, final article on publisher webpages)

  23. Soeren Nickel, Max Sondag, Wouter Meulemans, Markus Chimani, Stephen Kobourov, Jaakko Peltonen, and Martin Nöllenburg. Computing Stable Demers Cartograms. In proceedings of GD 2019, the 27th International Symposium on Graph Drawing and Network Visualization, pages 46-60, Springer, 2019. (preprint article in ArXiv, final article on publisher webpages)

  24. Chien Lu, Jaakko Peltonen and Timo Nummenmaa. Game Postmortems vs. Developer Reddit AMAs: Computational Analysis of Developer Communication. In proceedings of FDG 2019, International Conference on the Foundations of Digital Games, article 22, pages 1-7, ACM, 2019. (preprint pdf, final article on publisher webpages)

  25. Xiaozhou Li, Chien Lu, Jaakko Peltonen, and Zheying Zhang. A Statistical Analysis of Steam User Profiles towards Personalized Gamification. In proceedings of GamiFIN 2019, 3rd Annual International GamiFIN conference, pages 217-228, CEUR-WS, 2019. Award-winning: best paper award, GamiFIN 2019. (final open access article on publisher webpages)

  26. Elizaveta Zimina, Jyrki Nummenmaa, Kalervo Järvelin, Jaakko Peltonen, and Kostas Stefanidis. MuG-QA: Multilingual Grammatical Question Answering for RDF Data. In Proceedings of PIC 2018, International Conference on Progress in Informatics and Computing, pages 57-61, IEEE, 2018. Award-winning: best paper award, PIC 2018. (preprint pdf, final article on publisher webpages)

  27. Md Hijbul Alam*, Jaakko Peltonen*, Jyrki Nummenmaa, and Kalervo Järvelin. Author Tree-structured Hierarchical Dirichlet Process. In L. Soldatova, J. Vanschoren, G. Papadopoulos, and M. Ceci, editors, Proceedings of DS 2018, the 21st International Conference on Discovery Science, LLNCS 11198, pages 311-327, Springer, 2018. (* equal contributions) (preprint pdf, final paper on publisher pages)

  28. Elizaveta Zimina, Jyrki Nummenmaa, Kalervo Järvelin, Jaakko Peltonen, Kostas Stefanidis and Heikki Hyyrö. GQA: Grammatical Question Answering for RDF Data. In Semantic Web Challenges : 5th SemWebEval Challenge at ESWC 2018, Heraklion, Greece, June 3-7, 2018, Revised Selected Papers, pages 82-97, Springer International Publishing, 2018. (preprint pdf, final paper on publisher pages)

  29. Md Hijbul Alam*, Jaakko Peltonen*, Jyrki Nummenmaa, and Kalervo Järvelin. Tree-structured Hierarchical Dirichlet Process. (* equal contributions) In S. Rodriguez, J. Prieto, P. Faria, S. Klos, A. Fernandez, S. Mazuelas, M. D. Jimenez-Lopez, M. N. Moreno, and E. M. Navarro Martinez, editors, Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference (Proceedings of DCAI 2018), pages 291-299, Springer, 2019. (preprint pdf, final paper on publisher pages)

  30. 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)

  31. 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)

  32. 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)

  33. 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)

  34. 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. (preprint pdf, final article on publisher webpages)

  35. 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)

  36. 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)

  37. 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)

  38. 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)

  39. 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)

  40. 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)

  41. 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)

  42. 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)

  43. 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)

  44. 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, 2014. (final pdf on publisher pages, supplemental document, code)

  45. 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)

  46. 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)

  47. 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)

  48. 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)

  49. 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. (preprint pdf, final paper on publisher pages)

  50. 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)

  51. 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)

  52. 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)

  53. 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)

  54. 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)

  55. 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)

  56. 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)

  57. 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, 2011. (abstract, final pdf on publisher pages, supplementary information)

  58. 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)

  59. 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)

  60. 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)

  61. 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.)

  62. 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

  63. 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)

  64. 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)

  65. 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.

  66. 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)

  67. 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)

  68. 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)

  69. 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)

  70. 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, final article on publisher webpages)

  71. 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, final article on publisher webpages)

  72. 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)

  73. 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, International Conference, Madrid, Spain, August 2002, Proceedings, pp. 999-1004. Springer, 2002. (abstract, postscript, gzipped postscript, pdf) © Springer-Verlag

  74. 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)

  75. 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. (preprint pdf)

Publications as Editor

  1. Tat-Seng Chua, Norbert Fuhr, Gregory Grefenstette, Kalervo Järvelin, Jaakko Peltonen, and Nicolás Diaz Ferreyra, editors. User-Generated Content in Social Media (Report from Dagstuhl Seminar 17301). Dagstuhl Reports, Vol. 7, Issue 7, 2018. (final open access report on publisher webpages)

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

Other Scientific Publications

  1. Meri Kulmala, Pirjo Lindfors, Jaakko Peltonen, Virve Pekurinen, Tuula Nygård, ja Anna-Maija Multas. Tubettajat nuorten mielenterveyden vertaistukijoina sosiaalisessa mediassa - Mitä ja miten tutkia, ja kenen kanssa? Sosiaalitieteellinen aikakauslehti, 60: 474–477, 2023. (final open access article on publisher webpages)

  2. Mari Hatavara, Matti Hyvärinen, Nanny Jolma, Jussi Kurunmäki, Jani Marjanen, Jyrki Nummenmaa, Timo Nummenmaa, Jaakko Peltonen, Martin Pettersson, Hanna Rautajoki, Kirsi Sandberg, Kari Teräs, and Risto Turunen. Parlamentaarisen politiikan ajat. In Politiikasta.fi, 2023. (final open access text on publisher pages)

  3. Abel Szkalisity, Filippo Piccinini, Attila Beleon, Tamas Balassa, Istvan Gergely Varga, Ede Migh, Lassi Paavolainen, Sanna Timonen, Indranil Banerjee, Yohei Yamauchi, Istvan Ando, Jaakko Peltonen, Vilja Pietiäinen, Viktor Honti, and Peter Horvath. Regression plane concept: analysing continuous cellular processes with machine learning. bioRxiv preprint, 2020. (preprint on bioRxiv)

  4. Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, and Samuel Kaski. Scalable Probabilistic Matrix Factorization with Graph-Based Priors. ArXiv preprint, arXiv:1908.09393 [cs], 2019. (preprint on arXiv)

  5. Jaakko Peltonen. Machine Learning for Analysis of Hierarchical Conversation Forums. Abstract in Tat-Seng Chua, Norbert Fuhr, Gregory Grefenstette, Kalervo Järvelin, Jaakko Peltonen, and Nicolás Diaz Ferreyra, editors, User-Generated Content in Social Media (Report from Dagstuhl Seminar 17301). Dagstuhl Reports, Vol. 7, Issue 7, page 121, 2018. (final open access report on publisher webpages)

  6. 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) (preprint on arXiv)

  7. 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.

  8. 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, final abstract on publisher pages)

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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. (preprint on arXiv)

  15. 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 EA '14: CHI '14 Extended Abstracts on Human Factors in Computing Systems, pages 455-458, ACM, 2014. (final paper on publisher pages)

  16. 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)

  17. 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)

  18. 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.

  19. 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)

  20. 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.

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

  22. 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.

  23. 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)

  24. 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)

  25. 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)

  26. 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)

  27. 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.

Publications intended for professional communities

  1. Adeline Philippa Clarke, Krista Lagus, Katja Heta Laine, Maria Litova, Matti Nelimarkka, Joni Oksanen, Jaakko Peltonen, Tuukka Samuli Oikarinen, Jani-Matti Tirkkonen, Ida Toivanen, Maria Valaste. `finnsurveytext' software package. CRAN, 2024. (final package on CRAN webpages)

  2. Jacob Rubæk Holm, Martin Henning, Jaakko Peltonen, Bram Timmermans. Academic teaching and AI: The central role of policies. Nordic AI-BEST workshop summary report, 2024. (PDF at project partner webpages)

  3. Jacob Rubæk Holm, Jaakko Peltonen, Bram Timmermans, and Martin Henning. Academic teaching: Local university policies for generative AI and students’ use of generative AI as a personalized tutor. Nordic AI-BEST workshop summary report, 2024.

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.
  • Jaakko Peltonen, AI Helsinki Seminar, January 28, 2019: Exploring Online Discussion with Probabilistic Models. An overview of our work on topic modeling and interactive social media exploration. (materials of the talk online)
  • Aalto University, Machine Learning Coffee Seminar, November 26, 2018: Exploring Large And Hierarchical Online Discussion Venues With Probabilistic Models. An overview of our work on deep hierarhical topic modeling and interactive exploration of social media discussion forums. (video of the talk available on YouTube)
  • University of Tampere, December 8, 2015: Statistical approaches for visual exploratory data analysis. An overview of selected exploratory data analysis and visualization works.
  • University of Pittsburgh, September 2, 2015: An information retrieval approach to visualization of high-dimensional data. An overview of selected visualization works. (pdf slides, announcement of the talk in the CoMeT system)
  • University of Pittsburgh, September 1, 2015: Lost in Publications? How to Find Your Way in 50 Million Scientific Documents. Describes the work on information seeking and cross-system transfer of open user models contained in the CIKM 2013 and UMAP 2015 publications. (pdf slides, announcement of the talk in the CoMeT system)
  • University of Tampere, Methods Festival 2015, August 20, 2015: Better Information Seeking through Statistics: How to Find Your Way in 50 Million Scientific Documents.
  • University of Szeged, Hungary, February 6, 2015: Lost in Publications? How to Find Your Way in 50 Million Scientific Documents.

Some Useful Resources

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


Latest News:

New: open positions for doctoral researchers in 3-year doctoral program pilot of the Finnish Doctoral Program Network in Artificial Intelligence. Choose Jaakko Peltonen as your supervisor. Apply now! Deadline to apply: April 2, 2024.

New: open position for doctoral researcher in Game Culture Research and Data Science. Application deadline was March 5, 2024, applications are currently under review.