(aside image)
Non-parametric Bayesian clustering of gene expression and protein concentration reveals information on post-translational regulation (see Infinite Factorization of Multiple Non-parametric Views).

ARTO KLAMI


I am a post-doctoral researcher in the Statistical Machine Learning and Bioinformatics group in the Department of Information and Computer Science of the Aalto University School of Science. I am also a member of Helsinki Institute for Information Technology HIIT and PASCAL2 EU Network of Excellence for pattern recognition.

I work on an Academy of Finland postdoctoral research project titled Nonparametric Bayesian methods for dependency modeling. My research interests include exploratory data analysis, dependency modeling, and (non-parametric) Bayesian learning. I develop novel computational methods for the task of extracting statistical dependencies between multiple data sources, and apply them in a variety of application fields, including analysis of brain imaging data of naturalistic stimulation, bioinformatics, and understanding and utilizing eye movements in cognitive interfaces.

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

Contact

Teaching

In fall 2010 I co-lectured the course T-61.6040 Special Course in Computer and Information Science, with the topic of Learning from multiple sources.

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

Publications

Journal publications


  1. 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, to appear.

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

  3. 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)

  4. Simon Rogers, Arto Klami, Janne Sinkkonen, Mark Girolami, Samuel Kaski. Infinite Factorization of Multiple Non-parametric Views. Machine Learning, 2010. DOI 10.1007/s10994-009-5155-1. (online)

  5. 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)

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

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

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

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

Refereed conference publications


  1. Seppo Virtanen, Arto Klami, Suleiman A. Khan, Samuel Kaski. Bayesian Group Factor Analysis. To appear in AISTATS, 2012. (preliminary version in arXiv.)

  2. Seppo Virtanen, Arto Klami, 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.)

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

  4. 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)

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

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

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

  8. 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)

  9. László 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)

  10. 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)

  11. 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)

  12. 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)

  13. 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)

  14. 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)

  15. 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)

  16. 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)

  17. 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)

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

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)