Department of Computer Science

Arto Klami

I lead the Multi-source probabilistic inference subgroup of the Complex Systems Computation (CoSCo) group at the Department of Computer Science of University of Helsinki. I am also a member of Helsinki Institute for Information Technology HIIT and The Finnish Center of Excellence in Computational Inference Research (COIN). Until the end of 2012 I was a postdoctoral researcher at the Department of Information and Computer Science, Aalto University, and between March 2015 and June 2015 I was a Visiting Research Scientist at Amazon Berlin.

My research interests are in Bayesian modeling of complex data collections. I lead the project "Traces of Information: Intelligence from fragmented data", funded by the Academy of Finland for 2013-2019, which aims at extracting useful intelligence about individuals, groups and communities by combined analysis of seemingly disparate sources of information, such as social media output, spatiotemporal data recorded by various devices, and public data sources. I also lead the "Scalable probabilistic analytics (SPA)" project funded by Tekes Industrial Internet program and three companies (M-Brain, Reaktor and Ekahau), which develops computationally efficient probabilistic programming tools for speeding up the development of probabilistic models for data analytics and industrial internet applications.

In 2011 I organized a PASCAL challenge on MEG Mind Reading.

Contact

  • Postal address: Department of Computer Science, P.O.Box 68, FIN-00014 UNIVERSITY OF HELSINKI, Finland
  • Physical address: Room A311, Exactum, Gustaf Hällströmin katu 2b, Helsinki
  • Tel: +358-9-191 51261
  • Email: arto.klami'at'cs.helsinki.fi

Teaching

In fall 2016 I am giving the course Seminar on probabilistic programming together with Antti Honkela.

In spring 2016 I lectured the Advanced course in machine learning.

In fall 2014 I gave the course Seminar in probabilistic models for big data together with Antti Honkela.

In fall 2010 I gave the seminar course Learning from multiple sources together with Jaakko Peltonen.

In the past I have taken part in teaching, for example, modeling of biological networks, data analysis for gene expression, and co-occurrence methods in analysis of discrete data.

Software

R implementations for Bayesian canonical correlation analysis and group factor analysis are available in package CCAGFA, and the implementation for collective matrix factorization in package CMF.

Publications

Journal publications

  1. Jussi Korpela, Andreas Henelius, Lauri Ahonen, Arto Klami, and Kai Puolamäki. Using regression makes extraction of shared variation in multiple datasets easy. Data Mining and Knowledge Discovery, 30(5):1112-1133, 2016 (html).

  2. Jukka-Pekka Kauppi, Melih Kandemir, Veli-Matti Saarinen, Lotta Hirvenkari, Lauri Parkkonen, Arto Klami, Riitta Hari, and Samuel Kaski. Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals. NeuroImage, 112:288--298, 2015 (doi).

  3. Arto Klami, Seppo Virtanen, Eemeli Leppäaho, and Samuel Kaski. Group factor analysis. IEEE Transactions on Neural Networks and Learning Systems, 26(9):2136--2147, 2015. (arXiv preprint, doi)

  4. Melih Kandemir, Akos Vetek, Mehmet Gönen, Arto Klami, and Samuel Kaski. Multi-task and multi-view learning of user state. Neurocomputing, 139:97-106, 2014. (online)

  5. Arto Klami. Bayesian object matching. Machine Learning, 92(2):225-250, 2013. (doi,pdf preprint)

  6. Arto Klami, Seppo Virtanen, Samuel Kaski. Bayesian canonical correlation analysis. Journal of Machine Learning Research, 14:965-1003, 2013. (pdf)

  7. Miika Koskinen, Jaakko Viinikanoja, Mikko Kurimo, Arto Klami, Samuel Kaski, and Riitta Hari. Identifying fragments of natural speech from the listener's MEG signals. Human Brain Mapping, 34(6):1477-1489, 2012. (online)

  8. Abhishek Tripathi, Arto Klami, Matej Orešič and Samuel Kaski. Matching samples of multiple views. Data Mining and Knowledge Discovery, 23(2):300-321, 2011. (online)

  9. Suvi Savola, Arto Klami, Samuel Myllykangas, Cristina Manara, Katia Scotlandi, Piero Ricci, Sakari Knuutila, and Jukka Vakkila. High Expression of Complement Component 5 (C5) at Tumor Site Associates with Superior Survival in Ewing's Sarcoma Family of Tumour Patients. ISRN Oncology, Volume 2011, Article ID 168712, 2011. (online)

  10. Simon Rogers, Arto Klami, Janne Sinkkonen, Mark Girolami, and Samuel Kaski. Infinite Factorization of Multiple Non-parametric Views. Machine Learning, 79(1-2):201-226, 2010. (online)

  11. Suvi Savola, Arto Klami, Abhishek Tripathi, Tarja Niini, Massimo Serra, Piero Picci, Samuel Kaski, Diana Zambelli, Katia Scotlandi, and Sakari Knuutila. Combined use of expression and CGH arrays pinpoints novel candidate genes in Ewing sarcoma family of tumors. BMC Cancer 9:17, 2009. (html)

  12. Arto Klami and Samuel Kaski. Probabilistic approach to detecting dependencies between data sets. Neurocomputing, 72(1-3):39-46, 2008. (abstract, doi).

  13. Abhishek Tripathi, Arto Klami, and Samuel Kaski. Simple integrative preprocessing preserves what is shared in data sources. BMC Bioinformatics, 9:111, 2008. (html)

  14. Samuel Kaski, Janne Sinkkonen, and Arto Klami. Discriminative Clustering. Neurocomputing, 69:18-41, 2005. (preprint abstract, preprint pdf)

  15. Jaakko Peltonen, Arto Klami, and Samuel Kaski. Improved Learning of Riemannian Metrics for Exploratory Data Analysis. Neural Networks, 17:1087-1100, 2004. (abstract, Elsevier page linking the final paper,erratum to final paper on Elsevier pages)

Refereed conference and workshop publications

  1. Arto Klami and Aditya Jitta. Probabilistic size-constrained microclustering. In Proceedings of Uncertainty in Artificial Intelligence (UAI), 2016 (pdf).

  2. Juho Leinonen, Krista Longi, Arto Klami, Alireza Ahadi, and Arto Vihavainen. Typing patterns and authentication in practical programming exams. In Proceedings of ITiCSE, 2016.

  3. Juho Leinonen, Krista Longi, Arto Klami, and Arto Vihavainen. Automatic inference of programming performance and experience from typing patterns. In Proceedings of SIGCSE, 2016.

  4. Krista Longi, Juho Leinonen, Henrik Nygren, Joni Salmi, Arto Klami, and Arto Vihavainen. Identification of programmers from typing patterns. In Proceedings of Koli Calling, 2015. (doi)

  5. Arto Klami, Abhishek Tripathi, Johannes Sirola, Lauri Väre, and Frederic Roulland. Latent feature regression for multivariate count data. In Proceedings of Artificial Intelligence and Statistics, Volume 38 of JMLR C&WP, 2015. (pdf)

  6. Salvatore Andolina, Khalil Klouche, Jaakko Peltonen, Mohammad Hoque, Tuukka Ruotsalo, Diogo Cabral, Arto Klami, Dorota Glowacka, Patrik Flor\'{e}en, and Giulio Jacucci. IntentStreams: Smart parallel search streams for branching exploratory search. In Proceedings of the 20th Intelligent user interfaces (IUI) conference, 2015. (doi)

  7. Arto Klami. Polya-gamma augmentations for factor models. In Asian Conference on Machine Learning, volume 39 of JMLR C&WP, 2014. (pdf)

  8. Arto Klami, Guillaume Bouchard, and Abhishek Tripathi. Group-sparse embeddings in collective matrix factorization. In International Conference on Learning Representations, 2014. (arXiv preprint)

  9. Sami Remes, Arto Klami, and Samuel Kaski. Characterizing unknown events in MEG data with group factor analysis. In Proceedings of the 3rd Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI), 2013. (pdf)

  10. Sourav Bhattacharya, Santi Phithakkitnukoon, Petteri Nurmi, Arto Klami, Marco Veloso, and Carlos Bento. Gaussian process-based predictive modeling for bus ridership. In Proceedings of the 3rd International Workshop on Pervasive Urban Applications (PURBA), 2013. (pdf)

  11. Arto Klami. Variational Bayesian matching. In Proceedings of 4th Asian Conference on Machine Learning (ACML), volume 25 of JMLR C&WP, pp. 205-220, 2012. (pdf). ACML best paper award.

  12. Melih Kandemir, Arto Klami, Akos Vetek, and Samuel Kaski. Unsupervised inference of auditory attention from biosensors. In Proceedings of European Conference on Machine Learning (ECML), 2012. (preprint pdf)

  13. Seppo Virtanen, Janqging Jia, Arto Klami, and Trevor Darrell. Factorized multi-modal topic model. In Proceedings of the 28th conference on Uncertainty in Artificial Intelligence (UAI), 2012. (preprint pdf)

  14. Seppo Virtanen, Arto Klami, Suleiman A. Khan, and Samuel Kaski. Bayesian Group Factor Analysis. In Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS), volume 22 of JMLR C&WP, pp. 1269-1277, 2012. (pdf)

  15. Seppo Virtanen, Arto Klami, and Samuel Kaski. Bayesian CCA via Group Sparsity. In Proceedings of the 28th International Conference on Machine Learning (ICML), 2011. (code, pdf, see also a related poster abstract in the ICML 2011 Structured Sparsity workshop)

  16. Jaakko Viinikanoja, Arto Klami, and Samuel Kaski. Variational Bayesian mixture of robust CCA models. In Balcazar J.L. et al. (Eds): Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, pp. 370-385, 2010. (code, pdf)

  17. Arto Klami. Inferring Task-relevant Image Regions from Gaze Data. In IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 101-106, 2010. (online)

  18. Abhishek Tripathi, Arto Klami, and Sami Virpioja. Bilingual Sentence Matching Using Kernel CCA. In IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 130-135, 2010. (online)

  19. Peter Auer, Zakria Hussain, Samuel Kaski, Arto Klami, Jussi Kujala, Jorma Laaksonen, Alex P. Leung, Kitsuchart Pasupa, and John Shawe-Taylor. Pinview: Implicit Feedback in Content-Based Image Retrieval. In Proceedings of Workshop on Applications of Pattern Analysis, 2010. (pdf)

  20. Arto Klami, Seppo Virtanen, and Samuel Kaski. Bayesian Exponential Family Projections for Coupled Data Sources. In Uncertainty in Artificial Intelligence (UAI) 2010. (pdf)

  21. Kitsuchart Pasupa, Craig Saunders, Sandor Szedmak, Arto Klami, Samuel Kaski, and Steve Gunn. Learning to Rank Images from Eye Movements. In Proceedings of ICCV'2009 Workshop on Human-Computer Interaction (HCI'2009), pp. 2009-2016, 2009. (pdf)

  22. Laszlo Kozma, Arto Klami, and Samuel Kaski. GaZIR: Gaze-based Zooming Interface for Image Retrieval. In Proceedings of 11th Conference on Multimodal Interfaces and the 6th Workshop on Machine Learning for Multimodal Interaction (ICMI-MLMI), 2009. (pdf)

  23. Eerika Savia, Arto Klami, and Samuel Kaski. Fast Dependent Components for fMRI Analysis. In the IEEE 2009 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), pp. 1737-1740, 2009. (abstract, pdf)

  24. Abhishek Tripathi, Arto Klami, and Samuel Kaski. Using Dependencies to Pair Samples for Multi-View Learning. In the IEEE 2009 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), 2009. (abstract, pdf)

  25. Arto Klami, Craig Saunders, Teofilo de Campos, and Samuel Kaski. Can relevance of images be inferred from eye movements?. MIR'08: Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval, Vancouver, British Columbia, Canada, Oct 30-31, 2008. (abstract, pdf)

  26. Arto Klami and Samuel Kaski. Local Dependent Components. In Zoubin Ghahramani (Ed), Proceedings of the 24th International Conference on Machine Learning. 425-433. Omnipress, 2007. (abstract, preprint pdf)

  27. Arto Klami and Samuel Kaski. Generative models that discover dependencies between data sets. In Proceedings of Machine Learning for Signal Processing 2006. 123-128, 2006. (abstract, preprint pdf)

  28. Arto Klami and Samuel Kaski. Non-parametric Dependent Components. In Proceedings of ICASSP'05, IEEE International Conference on Acoustics, Speech, and Signal Processing, pages V-209 - V-212, IEEE, 2005. (abstract, pdf)

  29. 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, Saptember 2003. (abstract, postscript, gzipped postscript)

  30. Samuel Kaski, Janne Sinkkonen, and Arto Klami. Regularized Discriminative Clustering. In C. Molina, T.Adali, J.Larsen, M. Van Hulle, editors, Neural Networks for Signal Processing XIII, pages 289-298, IEEE, New York, 2003. (abstract, postscript, gzipped postscript, pdf)

  31. Jaakko Peltonen, Arto Klami, and Samuel Kaski. Learning More Accurate Metrics for Self-Organizing Maps. In Jose R. Dorronsoro, editor, Artificial Neural Networks - ICANN 2002, pages 999-1004. Springer, 2002. (abstract, postscript, gzipped postscript) © Springer-Verlag.

Non-refereed publications

  1. Zakria Hussain, Arto Klami, Jussi Kujala, Alex P. Leung, Kitsuchart Pasupa, Peter Auer, Samuel Kaski, Jorma Laaksonen, and John Shawe-Taylor. PinView: Implicit Feedback in Content-Based Image Retrieval. arXiv:1410.0471, 2014. (pdf)

  2. Riitta Hari and Arto Klami. Mistä aivotutkija tietää, mitä minä näen?. Tiede, 12:46-49, 2011. (Popular science article on brain decoding in a Finnish science magazine)

  3. Arto Klami, editor. Proceedings of ICANN/PASCAL2 Challenge: MEG Mind Reading, Aalto University Publication series SCIENCE+TECHNOLOGY 29/2011. Department of Information and Computer Science, 2011.(pdf)

  4. Arto Klami, Pavan Ramkumar, Seppo Virtanen, Lauri Parkkonen, Riitta Hari, and Samuel Kaski. ICANN/PASCAL2 Challenge: MEG mind reading - overview and results. In Proceedings of ICANN/PASCAL2 Challenge: MEG Mind Reading, Aalto University Publication series SCIENCE+TECHNOLOGY 29/2011, pages 3-19, 2011. (pdf, erratum)

Theses

  1. Arto Klami Modeling of mutual dependencies. PhD Thesis, Helsinki University of Technology, Faculty of Information and Natural Sciences, 2008. (Electronic version)

  2. Arto Klami Regularized Discriminative Clustering. Master's Thesis, Helsinki University of Technology, Department of Engineering Physics and Mathematics, 2003. (PDF)

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arto.klami@cs.Helsinki.fi Last update 22.01.2016