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Publications Puolamaki Kai
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List of publications

1 June 2022

Kai Puolamäki, Docent, PhD

Associate Professor (computer science and atmospheric sciences)

Department of Computer Science & Institute for Atmospheric and Earth System Research

University of Helsinki, Finland

ORCID iD 0000-0003-1819-1047

Personal homepage: https://www.iki.fi/kaip 

I have 87 peer-reviewed scientific articles of which 50 are journal papers. The 56 articles which have been cited at least 10 times are shown below with a tag [highly cited] and those with at least 20 citations with a red tag [highly cited]. The citation counts are from Google Scholar on 27 April 2022.[1]

A Peer-reviewed scientific articles

Scientific articles in refereed scientific journals

1. Rafael Savvides, Andreas Henelius, Emilia Oikarinen, Kai Puolamäki. Visual Data Exploration as a Statistical Testing Procedure: Within-view and Between-view Multiple Comparisons. IEEE Transactions on Visualization and Computer Graphics. Epub ahead of print. https://doi.org/10.1109/TVCG.2022.3175532 

2. Tuula Räsänen, Arto Reiman, Kai Puolamäki, Rafael Savvides, Emilia Oikarinen, Eero Lantto. Finding statistically significant high accident counts in exploration of occupational accident data. Journal of Safety Research. Epub ahead of print. https://doi.org/10.1016/j.jsr.2022.04.003 

3. Anton Björklund, Andreas Henelius, Emilia Oikarinen, Kimmo Kallonen, Kai Puolamäki. Robust regression via error tolerance. Data Mining and Knowledge Discovery. 36(2): 780-810, 2022. https://doi.org/10.1007/s10618-022-00819-2 

4. Jarmo Mäkelä, Laila Melkas, Ivan Mammarella, Tuomo Nieminen, Suyog Halasinamara Chandramouli, Rafael Savvides, Kai Puolamäki. Technical note: Incorporating expert domain knowledge into causal structure discovery workflows. Biogeosciences, 19: 2095–2099, 2022. https://doi.org/10.5194/bg-19-2095-2022 

5. Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, Kai Puolamäki. Machine learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets. Geoscientific Model Development, 14: 7411–7424, 2021. https://doi.org/10.5194/gmd-14-7411-2021 

6. Kai Puolamäki, Emilia Oikarinen, Andreas Henelius. Guided Visual Exploration of Relations in Data Sets. Journal of Machine Learning Research, 22(96): 1-32, 2021. https://jmlr.org/papers/v22/19-364.html

7. Francesco Concas, Julien Mineraud, Eemil Lagerspetz, Samu Varjonen, Xiaoli Liu, Kai Puolamäki, Petteri Nurmi, Sasu Tarkoma. Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration: A Survey and Critical Analysis. ACM Transactions on Sensor Networks, 17(2): 1-44, 2021. https://doi.org/10.1145/3446005 

8. Emilia Oikarinen, Henri Elias Tiittanen, Andreas Henelius, Kai Puolamäki. Detecting virtual concept drift of regressors without ground truth values. Data Mining and Knowledge Discovery, 35: 726–747, 2021. https://doi.org/10.1007/s10618-021-00739-7

9. Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie. Interactive visual data exploration with subjective feedback: an information-theoretic approach. Data Mining and Knowledge Discovery 34(1): 21-49, 2020. https://doi.org/10.1007/s10618-019-00655-x

10. Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie. A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback. IEEE Transactions on Knowledge and Data Engineering, 32(9): 1666-1679, 2020. https://doi.org/10.1109/TKDE.2019.2907082 

11. [highly cited] Virpi Kalakoski, Andreas Henelius, Emilia Oikarinen, Antti Ukkonen, Kai Puolamäki. Cognitive ergonomics for data analysis. Experimental study of cognitive limitations in a data-based judgement task. Behaviour & Information Technology, 2019. https://doi.org/10.1080/0144929X.2019.1657181 

12. Kai Puolamäki, Andreas Henelius, Antti Ukkonen. Randomization algorithms for large sparse networks. Physical Review E 99(5): 053311, 2019. https://doi.org/10.1103/PhysRevE.99.053311 

13. [highly cited] Lauri Ahonen, Benjamin Ultan Cowley, Arto Hellas, Kai Puolamäki. Biosignals reflect pair-dynamics in collaborative work: EDA and ECG study of pair-programming in a classroom environment. Scientific Reports 8(1): 3138, 2018. https://doi.org/10.1038/s41598-018-21518-3

14. [highly cited] Miika Toivanen, Kristian Lukander, Kai Puolamäki. Probabilistic approach to robust wearable gaze tracking. Journal of Eye Movement Research, 10(4), 2017. https://doi.org/10.16910/jemr.10.4.2 

15. Indrė Žliobaitė, Kai Puolamäki, Jussi T. Eronen, Mikael Fortelius. A survey of computational methods for fossil data analysis. Evolutionary Ecology Research, 18: 466-502, 2017. http://www.evolutionary-ecology.com/abstracts/v18/3066.html 

16. Kristian Lukander, Miika Toivanen, Kai Puolamäki. Inferring intent and action from gaze in naturalistic behaviour - a review. International Journal of Mobile Human Computer Interaction, 9(4): 41-57, 2017. https://doi.org/10.4018/IJMHCI.2017100104 

17. Jussi Korpela, Andreas Henelius, Lauri Ahonen, Arto Klami, Kai Puolamäki. Using regression makes extraction of shared variation in multiple datasets easy. Data Mining and Knowledge Discovery, 30(5): 1112-1133, 2016. https://doi.org/10.1007/s10618-016-0465-y 

18. [highly cited] Lauri Ahonen, Benjamin Cowley, Jari Torniainen, Antti Ukkonen, Arto Vihavainen, Kai Puolamäki. Cognitive Collaboration Found in Cardiac Physiology: Study in Classroom Environment. PLoS ONE 11(7): e0159178, 2016. https://doi.org/10.1371/journal.pone.0159178 

19. [highly cited] Jefrey Lijffijt, Terttu Nevalainen, Tanja Säily, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila. Significance testing of word frequencies in corpora. Literary and Linguistic Computing, 31(2): 374-397, 2016. https://doi.org/10.1093/llc/fqu064 

20. Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki. Size matters: choosing the most informative set of window lengths for mining patterns in event sequences. Data Mining and Knowledge Discovery, 29(6): 1838-1864, 2015. https://doi.org/10.1007/s10618-014-0397-3 

21. [highly cited] Jussi Korpela, Kai Puolamäki, Aristides Gionis. Confidence bands for time series data. Data Mining and Knowledge Discovery, 28(5-6): 1530-1553, 2014. https://doi.org/10.1007/s10618-014-0371-0

22. [highly cited] Andreas Henelius, Kai Puolamäki, Henrik Boström, Lars Asker, Panagiotis Papapetrou. A peek into the black box: exploring classifiers by randomization. Data Mining and Knowledge Discovery, 28(5-6): 1503-1529, 2014. https://doi.org/10.1007/s10618-014-0368-8 

23. [highly cited] Mikael Fortelius, Jussi T. Eronen, Ferhat Kaya, Hui Tang, and Kai Puolamäki. Evolution of Neogene Mammals in Eurasia: Environmental Forcing and Biotic Interactions. Annual Review of Earth and Planetary Sciences, 42: 579-604, 2014. https://doi.org/10.1146/annurev-earth-050212-124030 

24. [highly cited] Andreas Henelius, Mikael Sallinen, Minna Huotilainen, Kiti Müller, Jussi Virkkala, and Kai Puolamäki. Heart Rate Variability for Evaluating Vigilant Attention in Partial Chronic Sleep Restriction. Sleep, 37(7): 1257-1267, 2014. https://doi.org/10.5665/sleep.3850 

25. [highly cited] Jefrey Lijffijt, Panagiotis Papapetrou, and Kai Puolamäki. A statistical significance testing approach to mining the most informative set of patterns. Data Mining and Knowledge Discovery, 28(1):238–263, 2014. https://doi.org/10.1007/s10618-012-0298-2 

26. [highly cited] Sirpa Nummela, Henry Pihlström, Kai Puolamäki, Mikael Fortelius, Simo Hemilä, and Tom Reuter. Exploring the mammalian sensory space: co-operations and trade-offs among senses. Journal of Comparative Physiology A, 199(12):1077–1092, 2013. https://doi.org/10.1007/s00359-013-0846-2 

27. Hannes Gamper, Christina Dicke, Mark Billinghurst, and Kai Puolamäki. Sound sample detection and numerosity estimation using auditory display. ACM Transactions on Applied Perception, 10(1):4:1–4:18, 2013. https://doi.org/10.1145/2422105.2422109 

28. [highly cited] Jussi T. Eronen, M. Fortelius, F.T. Portmann, K. Puolamäki, and Christine M. Janis. Neogene aridification of the Northern Hemisphere. Geology, 40(9):823–826, 2012. https://doi.org/10.1130/G33147.1 

29. [highly cited] Liping Liu, Kai Puolamäki, Jussi T. Eronen, Majid M. Ataabadi, Elina Hernesniemi, and Mikael Fortelius. Dental functional traits of mammals resolve productivity in terrestrial ecosystems past and present. Proceedings of the Royal Society B, 279(1739):2793–2799, 2012. https://doi.org/10.1098/rspb.2012.0211 

30. Jussi T. Eronen, Kai Puolamäki, Hannes Heikinheimo, Heikki Lokki, Ari Venäläinen, Heikki Mannila, and Mikael Fortelius. The effect of scale, climate and environment on species richness and spatial distribution of Finnish birds. Annales Zoologici Fennici, 48(5):257–274, 2011. http://www.sekj.org/PDF/anz48-free/anz48-257.pdf 

31. [highly cited] Antti Ajanki, Mark Billinghurst, Hannes Gamper, Toni Järvenpää, Melih Kandemir, Samuel Kaski, Markus Koskela, Mikko Kurimo, Jorma Laaksonen, Kai Puolamäki, Teemu Ruokolainen, and Timo Tossavainen. An augmented reality interface to contextual information. Virtual Reality, 15(2-3):161–173, 2011. https://doi.org/10.1007/s10055-010-0183-5 

32. [highly cited] Aleksi Kallio, Kai Puolamäki, Mikael Fortelius, and Heikki Mannila. Correlations and co-occurrences of taxa: the role of temporal, geographic and taxonomic restrictions. Palaeontologia Electronica, 14(1): 4A, 2011. http://palaeo-electronica.org/2011_1/222/index.html 

33. [highly cited] J. T. Eronen, K. Puolamäki, L. Liu, K. Lintulaakso, J. Damuth, C. Janis, and M. Fortelius. Precipitation and large herbivorous mammals, part I: Estimates from present-day communities. Evolutionary Ecology Research, 12(2):217–233, 2010. http://www.evolutionary-ecology.com/issues/v12/n02/ggar2538.pdf 

34. [highly cited] J. T. Eronen, K. Puolamäki, L. Liu, K. Lintulaakso, J. Damuth, C. Janis, and M. Fortelius. Precipitation and large herbivorous mammals, part II: Application to fossil data. Evolutionary Ecology Research, 12(2):235–248, 2010. http://www.evolutionary-ecology.com/issues/v12/n02/hhar2539.pdf 

35. [highly cited] Antti Ajanki, David Hardoon, Samuel Kaski, Kai Puolamäki, and John Shawe-Taylor. Can eyes reveal interest? Implicit queries from gaze patterns. User Modeling and User-Adapted Interaction, 19(4):307–339, 2009. https://doi.org/10.1007/s11257-009-9066-4 

36. [highly cited] Antti Ukkonen, Kai Puolamäki, Aristides Gionis, and Heikki Mannila. A randomized approximation algorithm for computing bucket orders. Information Processing Letters, 109(7):356–359, 2009. https://doi.org/10.1016/j.ipl.2008.12.003 

37. [highly cited] Eerika Savia, Kai Puolamäki, and Samuel Kaski. Latent grouping models for user preference prediction. Machine Learning, 74(1):75–109, 2009. https://doi.org/10.1007/s10994-008-5081-7 

38. [highly cited] Kai Puolamäki, Sami Hanhijärvi, and Gemma C. Garriga. An approximation ratio for biclustering. Information Processing Letters, 108(2):45–49, 2008. https://doi.org/10.1016/j.ipl.2008.03.013 

39. [highly cited] Kai Puolamäki, Mikael Fortelius, and Heikki Mannila. Seriation in paleontological data using Markov chain Monte Carlo methods. PLoS Computational Biology, 2(2):e6, 2006. https://doi.org/10.1371/journal.pcbi.0020006 

40. Kai Puolamäki. Higgs sector and R-parity breaking couplings in models with broken U(1)B-L gauge symmetry. Physical Review D, 62(5):055010, 2000. https://doi.org/10.1103/PhysRevD.62.055010 

41. [highly cited] Katri Huitu, Yoshiharu Kawamura, Tatsuo Kobayashi, and Kai Puolamäki. Generic gravitational corrections to gauge couplings in SUSY SU(5) GUTs. Physics Letters B, 468(1–2):111–117, 1999. https://doi.org/10.1016/S0370-2693(99)01196-X 

42. [highly cited] Mariana Frank, Homayun Hamidian, and Kai Puolamäki. Supersymmetric spectrum in SO(10) GUTs with gauge-mediated supersymmetry breaking. Physical Review D, 60(9):095011, 1999. https://doi.org/10.1103/PhysRevD.60.095011 

43. [highly cited] Katri Huitu, Yoshiharu Kawamura, Tatsuo Kobayashi, and Kai Puolamäki. Phenomenological constraints on SUSY SU(5) GUTs with nonuniversal gaugino masses. Physical Review D, 61:035001, 1999. https://doi.org/10.1103/PhysRevD.61.035001 

44. [highly cited] Mariana Frank, Homayun Hamidian, and Kai Puolamäki. SO(10) GUTs with gauge mediated supersymmetry breaking. Physics Letters B, 456(2–4):179–184, 1999. https://doi.org/10.1016/S0370-2693(99)00506-7 

45. Katri Huitu, Kai Puolamäki, and Da-Xin Zhang. Critical basis dependence in bounding R-parity breaking couplings from neutral meson mixing. Physics Letters B, 446(3–4):285–289, 1999. https://doi.org/10.1016/S0370-2693(98)01532-9 

46. Homayun Hamidian, Katri Huitu, Kai Puolamäki, and Da-Xin Zhang. Radiative symmetry breaking and the b→sɣ decay in generalized GMSB models. Physics Letters B, 448(3–4):234–242, 1999. https://doi.org/10.1016/S0370-2693(99)00005-2 

47. [highly cited] Katri Huitu, Jukka Maalampi, and Kai Puolamäki. Signals of spontaneous R parity breaking at LEP and at a linear collider. The European Physical Journal C – Particles and Fields, 6(1):159–166, 1999. https://doi.org/10.1007/s100529800887 

48. [highly cited] Homayun Hamidian, Katri Huitu, Kai Puolamäki, and Da-Xin Zhang. Limits on tanβ in SU(5) GUTs with gauge-mediated supersymmetry breaking. Physics Letters B, 428(3–4):310–314, 1998. https://doi.org/10.1016/S0370-2693(98)00412-2 

49. [highly cited] Katri Huitu, Pran N. Pandita, and Kai Puolamäki. Mass of the lightest Higgs boson in supersymmetric left-right models. Physics Letters B, 423(1–2):97–103, 1998. https://doi.org/10.1016/S0370-2693(98)00086-0 

50. [highly cited] Katri Huitu, Pran N. Pandita, and Kai Puolamäki. Constraining the vacuum expectation values in naturally R-parity conserving supersymmetric models. Physics Letters B, 415(2):156–160, 1997. https://doi.org/10.1016/S0370-2693(97)01275-6 

Peer-reviewed articles in scientific anthologies or printed (including electronic) conference proceedings

51. Laila Melkas, Rafael Savvides, Suyog H. Chandramouli, Jarmo Mäkelä, Tuomo Nieminen, Ivan Mammarella, Kai Puolamäki. Interactive Causal Structure Discovery in Earth System Sciences. Proceedings of The KDD'21 Workshop on Causal Discovery.  Proceedings of Machine Learning Research, 150:3-25, 2021. http://proceedings.mlr.press/v150/melkas21a.html 

52. Anton Björklund, Andreas Henelius, Emilia Oikarinen, Kimmo Kallonen, Kai Puolamäki. Sparse Robust Regression for Explaining Classifiers. Discovery Science. DS 2019. Lecture Notes in Computer Science, vol 11828, 351-366, 2019. https://doi.org/10.1007/978-3-030-33778-0_27

53. Emilia Oikarinen, Kai Puolamäki, Samaneh Khoshrou, Mykola Pechenizkiy. Supervised Human-Guided Data Exploration. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019, 85-101, 2020. Communications in Computer and Information Science, vol 1167. https://doi.org/10.1007/978-3-030-43823-4_8 

54. Rafael Savvides, Andreas Henelius, Emilia Oikarinen, Kai Puolamäki. Significance of Patterns in Data Visualisations. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019), pp. 2509-1517, 2019. https://doi.org/10.1145/3292500.3330994 

55. Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, and Tijl De Bie. Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018), pp. 1208-1211. IEEE 2018. Extended version available at https://arxiv.org/abs/1710.08167.

56. [highly cited] Kai Puolamäki, Emilia Oikarinen, and Tijl De Bie. Subjectively Interesting Subgroup Discovery on Real-valued Targets. In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018), pp. 1352-1355. IEEE 2018. Extended version available at https://arxiv.org/abs/1710.04521.

57. Andreas Henelius, Emilia Oikarinen, and Kai Puolamäki. Tiler: Software for Human-Guided Data Exploration. To appear in Proceedings of ECML-PKDD 2018.  

58.  [highly cited] Andreas Henelius, Kai Puolamäki, Antti Ukkonen. Interpreting Classifiers through Attribute Interactions in Datasets. In Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017), pp. 8-13, 2017. Proceedings at https://arxiv.org/abs/1708.02666 and paper at http://arxiv.org/abs/1707.07576 

59. Jeremias Berg, Emilia Oikarinen, Matti Järvisalo, Kai Puolamäki. Minimum-Width Confidence Bands via Constraint Optimization. In Proc of the 23rd International Conference on Principles and Practice of Constraint Programming (CP 2017), to appear.

60. Jussi Korpela, Emilia Oikarinen, Kai Puolamäki. Multivariate Confidence Intervals. In Proceedings of the 2017 SIAM International Conference on Data Mining, pp. 696-704, 2017. https://doi.org/10.1137/1.9781611974973.78 Extended version is available at https://arxiv.org/abs/1701.05763 

61. Andreas Henelius, Isak Karlsson, Panagiotis Papapetrou, Antti Ukkonen, and Kai Puolamäki. Semigeometric Tiling of Event Sequences. ECML PKDD 2016, Part I, LNCS 9851, pp. 329-344, 2016. https://doi.org/10.1007/978-3-319-46128-1_21 

62. [highly cited] Kai Puolamäki, Bo Kang, Jefrey Lijffijt, Tijl De Bie. Interactive Visual Data Exploration with Subjective Feedback. ECML PKDD 2016, Part II, LNCS 9852, pp. 214-229, 2016. https://doi.org/10.1007/978-3-319-46227-1_14 

63. [highly cited] Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie. A Tool for Subjective and Interactive Visual Data Exploration. ECML PKDD 2016, Part III, LNCS 9853, pp. 3-7, 2016. https://doi.org/10.1007/978-3-319-46131-1_1 

64. [highly cited] Andreas Henelius, Kai Puolamäki, Isak Karlsson, Jing Zhao, Lars Asker, Henrik Boström, and Panagiotis Papapetrou. GoldenEye++: A Closer Look into the Black Box. Statistical Learning and Data Sciences, Lecture Notes in Computer Science:  9047:96-105, 2015. https://doi.org/10.1007/978-3-319-17091-6_5 

65. Andreas Henelius, Jussi Korpela, and Kai Puolamäki. Explaining Interval Sequences by Randomization. ECML PKDD 2013, Part I, LNCS 8188, pp. 337–352, 2013. https://doi.org/10.1007/978-3-642-40988-2_22 

66. [highly cited] Jefrey Lijffijt, Panagiotis Papapetrou, and Kai Puolamäki. Size Matters: Finding the Most Informative Set of Window Lengths. In Proceedings of ECML-PKDD 2012. Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science, 7524:451-466, 2012. https://doi.org/10.1007/978-3-642-33486-3_29 

67. [highly cited] Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki, and Heikki Mannila. Analyzing word frequencies in large text corpora using inter-arrival times and bootstrapping. In Proceedings of ECML-PKDD 2011. Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II, pages 341-357, 2011. https://doi.org/10.1007/978-3-642-23783-6_22 

68. [highly cited] A. Ajanki, M. Billinghurst, T. Järvenpää, M. Kandemir, S. Kaski M. Koskela, M. Kurimo, J. Laaksonen, K. Puolamäki, T. Ruokolainen, and T. Tossavainen. Contextual information access with augmented reality. In 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pages 95–100, 2010. https://doi.org/10.1109/MLSP.2010.5589228 

69. [highly cited] Kai Puolamäki, Panagiotis Papapetrou, and Jefrey Lijffijt. Visually controllable data mining methods. In IEEE International Conference on Data Mining Workshops 2010, 2010. https://doi.org/10.1109/ICDMW.2010.141 

70. Antti Ajanki, Mark Billinghurst, Melih Kandemir, Samuel Kaski, Markus Koskela, Jorma Laaksonen, Kai Puolamäki, and Timo Tossavainen. Ubiquitous contextual information access with proactive information retrieval and augmentation. In The Fourth International Workshop in Ubiquitous Augmented Reality (IWUVR 2010), 2010.

71. Tapio Lokki and Kai Puolamäki. Canonical analysis of individual vocabulary profiling data. In 2010 Second International Workshop on Quality of Multimedia Experience (QoMEX), pages 152–157, 2010. https://doi.org/10.1109/QOMEX.2010.5516320 

72. [highly cited] Kai Puolamäki and Samuel Kaski. Bayesian solutions to the label switching problem. In Advances in Intelligent Data Analysis VIII, Lecture Notes in Computer Science, pages 381–392, Berlin / Heidelberg, 2009. Springer. https://doi.org/10.1007/978-3-642-03915-7_33 

73. Eerika Savia, Kai Puolamäki, and Samuel Kaski. Two-way grouping by one-way topic models. In Advances in Intelligent Data Analysis VIII, Lecture Notes in Computer Science, pages 178–189, Berlin / Heidelberg, 2009. Springer. https://doi.org/10.1007/978-3-642-03915-7_16 

74. [highly cited] Sami Hanhijärvi, Markus Ojala, Niko Vuokko, Kai Puolamäki, Nikolaj Tatti, and Heikki Mannila. Tell me something I don't know: Randomization strategies for iterative data mining. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '09), pages 379-388, New York, NY, USA, 2009. ACM. https://doi.org/10.1145/1557019.1557065 

75. [highly cited] Sami Hanhijärvi, Gemma C. Garriga, and Kai Puolamäki. Randomization techniques for graphs. In Proceedings of the 9th SIAM International Conference on Data Mining (SDM '09), pages 780–791, 2009. http://www.siam.org/proceedings/datamining/2009/dm09_071_hanhijarvis.pdf 

76. [highly cited] Kai Puolamäki, Antti Ajanki, and Samuel Kaski. Learning to learn implicit queries from gaze patterns. In Proceedings of the 25th International Conference on Machine Learning (ICML '08), pages 760–767, New York, NY, USA, 2008. ACM. https://doi.org/10.1145/1390156.1390252 

77. Sami Hanhijärvi, Gemma C. Garriga, and Kai Puolamäki. Randomization techniques for statistical significance testing on graphs, 2008. Poster and extended abstract, 6th International Workshop on Mining and Learning with Graphs (MLG '08). [Peer-reviewed and published at the workshop web site, but with no formal proceedings] http://research.ics.aalto.fi/events/MLG08/posters.html 

78. Tapani Raiko, Kai Puolamäki, Juha Karhunen, Jaakko Hollmén, Antti Honkela, Heikki Mannila, Erkki Oja, and Olli Simula. Macadamia: Master's programme in machine learning and data mining. Teaching Machine Learning Workshop on Open Problems and New Directions, 2008.

79. [highly cited] David Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, and Samuel Kaski. Information retrieval by inferring implicit queries from eye movements. In International Conference on Artificial Intelligence and Statistics (AISTATS '07), 2007. http://jmlr.csail.mit.edu/proceedings/papers/v2/hardoon07a/hardoon07a.pdf 

80. [highly cited] Aristides Gionis, Heikki Mannila, Kai Puolamäki, and Antti Ukkonen. Algorithms for discovering bucket orders from data. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '06), pages 561–566, New York, NY, USA, 2006. ACM. https://doi.org/10.1145/1150402.1150468 

81. [highly cited] Jarkko Salojärvi, Kai Puolamäki, and Samuel Kaski. On discriminative joint density modeling. In Machine Learning: ECML 2005, volume 3720/2005 of Lecture Notes in Computer Science, pages 341–352, Berlin / Heidelberg, 2005. Springer. https://doi.org/10.1007/11564096_34 

82. [highly cited] Jarkko Salojärvi, Kai Puolamäki, and Samuel Kaski. Implicit relevance feedback from eye movements. In Artificial Neural Networks: Biological Inspirations – ICANN 2005, volume 3696/2005 of Lecture Notes in Computer Science, pages 513–518, Berlin / Heidelberg, 2005. Springer. https://doi.org/10.1007/11550822_80 

83. [highly cited] Kai Puolamäki, Jarkko Salojärvi, Eerika Savia, Jaana Simola, and Samuel Kaski. Combining eye movements and collaborative filtering for proactive information retrieval. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '05), pages 146–153, New York, NY, USA, 2005. ACM. https://doi.org/10.1145/1076034.1076062 

84. [highly cited] Jarkko Salojärvi, Kai Puolamäki, and Samuel Kaski. Expectation maximization algorithms for conditional likelihoods. In Proceedings of the 22nd International Conference on Machine Learning (ICML '05), pages 752–759, New York, NY, USA, 2005. ACM. https://doi.org/10.1145/1102351.1102446 

85. [highly cited] Eerika Savia ja Kai Puolamäki, Janne Sinkkonen, and Samuel Kaski. Two-way latent grouping model for user preference prediction. In Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence (UAI '05), pages 518–525, 2005. http://uai.sis.pitt.edu/papers/05/p518-savia.pdf 

86. [highly cited] Jarkko Salojärvi, Kai Puolamäki, and Samuel Kaski. Relevance feedback from eye movements for proactive information retrieval. In Proceedings of the Processing Sensory Information for Proactive Systems (PSIPS '04), 2004. http://eprints.pascal-network.org/archive/00000117/02/psips04.pdf 

87. Katri Huitu, Pran Pandita, and Kai Puolamäki. The lightest neutral and doubly charged Higgs bosons of supersymmetric left-right models. In Proceedings of the 4th International Workshop on Linear Colliders (LCWS 99), 1999. http://arxiv.org/abs/hep-ph/9910504 

B Non-reviewed scientific articles

Articles, surveys and editorials in non-peer-reviewed scientific journals, and editorials, surveys and (at the author's discretion) book reviews in refereed journal

88. Anton Björklund, Jarmo Mäkelä, Kai Puolamäki. SLISEMAP: Explainable Dimensionality Reduction. 2022. https://arxiv.org/abs/2201.04455 

89. Henri Tiittanen, Emilia Oikarinen, Andreas Henelius, Kai Puolamäki. Estimating regression errors without ground truth values. 2019. https://arxiv.org/abs/1910.04069 

90. Mona Kurppa, Moritz Johannes Lange, Henri Johannes Suominen, Emilia Oikarinen, Rafael Savvides, Leena Järvi, Kai Puolamäki. Applying machine learning to replicate large-eddy simulation results on urban pollutant dispersion. In Proceedings of The Center of Excellence in Atmospheric Science (CoE ATM) Annual Seminar 2019. Report series in aerosol science 226, 2019. http://www.faar.fi/wp-content/uploads/2019/11/CoE_proceedings_2019-compressed.pdf 

91. Francesco Concas, Julien Mineraud, Eemil Lagerspetz, Samu Varjonen, Kai Puolamäki, Petteri Nurmi, Sasu Tarkoma. A Gap Analysis of Low-Cost Outdoor Air Quality Sensor In-Field Calibration. 2019. https://arxiv.org/abs/1912.06384 

92. Kai Puolamäki, Emilia Oikarinen, Andreas Henelius. Guided Visual Exploration of Relations in Data Sets. arXiv:1905.02515 [stat.ML] https://arxiv.org/abs/1905.02515 

93. Kai Puolamäki, Remco Chang. Interactive / Visual Data Exploration Tutorial. In Automating Data Science  (Dagstuhl Seminar 18401), 2019. https://doi.org/10.4230/DagRep.8.9.154 

94. Kai Puolamäki. Tell Me Something I Don’t Already Know: Tools for Human-guided Data Analysis. In Automating Data Science  (Dagstuhl Seminar 18401), 2019. https://doi.org/10.4230/DagRep.8.9.154 

95. Kai Puolamäki, Emilia Oikarinen, Buse Gul Atli, Andreas Henelius. Human-guided data exploration using randomisation. 2018. arXiv:1805.07725 [stat.ML] https://arxiv.org/abs/1805.07725 

96. Andreas Henelius, Emilia Oikarinen, Kai Puolamäki. Human-Guided Data Exploration. 2018. arXiv:1804.03194 [stat.ML] https://arxiv.org/abs/1804.03194 

97. Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie. Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. 2017. arXiv:1710.08167 [stat.ML]. https://arxiv.org/abs/1710.08167 

98. Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie. Subjectively Interesting Subgroup Discovery on Real-valued Targets. 2017. arXiv:1710.04521 [stat.ML]. https://arxiv.org/abs/1710.04521 

99. Andreas Henelius, Kai Puolamäki, Henrik Boström, Panagiotis Papapetrou. Clustering with Confidence: Finding Clusters with Statistical Guarantees, 2016. arXiv:1612.08714 [stat.ML]. https://arxiv.org/abs/1612.08714 

100. [highly cited] Andreas Henelius, Antti Ukkonen, Kai Puolamäki. Finding Statistically Significant Attribute Interactions, 2016. arXiv:1612.07597 [stat.ML].  https://arxiv.org/abs/1612.07597 

101. Sami Hanhijärvi, Kai Puolamäki, and Gemma C. Garriga. Multiple hypothesis testing in pattern discovery, 2009. arXiv:0906.5263v1 [stat.ML]. http://arxiv.org/abs/0906.5263 

102. Tom Reuter, Sirpa Nummela, Henry Pihlström, Kai Puolamäki, and Mikael Fortelius. Mammalian sensory organs: Size and function, 2008. Talk given by TR at the VISIONARIUM VII meeting at Tvärminne Zoological Station, University of Helsinki.

103. Mikael Fortelius, Kai Puolamäki, Jukka Jernvall, Heikki Mannila, and Aristides Gionis. Data quality, signal detection, and methodological robusticity in the analysis of large fossil datasets, 2006. Talk given by MF at the 66th Annual Meeting of the Society of Vertebrate Paleontology, Ottawa, Ontario, Canada, 18–21 October 2006. Abstract appears in Journal of Vertebrate Paleontology, Volume 26, supplement to number 3.

104. Katri Huitu, Jukka Maalampi, Pran Pandita, Kai Puolamäki, Martti Raidal, and Nikolai Romanenko. Tests of the left-right electroweak model at linear collider, 1999. Part of "e+e- Linear Colliders: Physics and Detector Studies, Part F" (DESY). http://arxiv.org/abs/hep-ph/9912405 

105. Katri Huitu, Jukka Maalampi, Aarre Pietilä, Kai Puolamäki, and Martti Raidal. Direct tests of the left-right electroweak model at linear collider, 1997. Part of "e+e- Linear Colliders: Physics and Detector Studies, Part E" (DESY 97-123E, edited by R. Settles).

106. Katri Huitu, Pran N. Pandita, and Kai Puolamäki. Constraining the scales of supersymmetric left-right models. In Proceedings of the 5th International Conference on Physics Beyond the Standard Model, 1997. Talk given by KH. http://arxiv.org/abs/hep-ph/9708492 

107 Katri Huitu, Jukka Maalampi, and Kai Puolamäki. Phenomenology of SUSY-models with spontaneously broken R-parity. In Proceedings of the 5th International Conference on Physics Beyond the Standard Model, 1997. Talk given by KP. http://arxiv.org/abs/hep-ph/9708491 

Articles in departmental publication series

108. Jefrey Lijffijt, Panagiotis Papapetrou, Niko Vuokko, and Kai Puolamäki. The smallest set of constraints that explains the data: a randomization approach. Technical Report TKK-ICS-R31, Aalto University School of Science and Technology, Department of Information and Computer Science, May 2010.

109. Antti Ajanki, Mark Billinghurst, Melih Kandemir, Samuel Kaski, Markus Koskela, Mikko Kurimo, Jorma Laaksonen, Kai Puolamäki, and Timo Tossavainen. Ubiquitous contextual information access with proactive retrieval and augmentation. Technical Report TKK-ICS-R27, Helsinki University of Technology, Department of Information and Computer Science, Espoo, Finland, December 2009.

110. Paula Järvinen, Kai Puolamäki, Pekka Siltanen, and Markus Ylikerälä. Visual analytics. Final report. VTT Working Papers 117, VTT Technical Research Centre of Finland, Espoo, Finland, 2009.

111. Kai Puolamäki and Samuel Kaski. Bayesian solutions to the label switching problem. Technical Report TKK-ICS-R7, TKK Reports in Information and Computer Science, 2008.

112. [highly cited] Jarkko Salojärvi, Kai Puolamäki, Jaana Simola, Lauri Kovanen, Ilpo Kojo, and Samuel Kaski. Inferring relevance from eye movements: Feature extraction. Technical Report A82, Publications in Computer and Information Science, 2005. http://www.cis.hut.fi/eyechallenge2005/irem-2005-03-03.pdf 

113. Katri Huitu, Pran N. Pandita, and Kai Puolamäki. Phenomenology of light Higgs bosons in supersymmetric left-right models. Technical Report HIP-1999-16/TH, Helsinki Institute of Physics, 1999. http://arxiv.org/abs/hep-ph/9904388 

114. Kai Puolamäki. On Higgs processes in electron-positron colliders. Technical Report HU-SEFT-R-1995-17, Research Institute for High Energy Physics (SEFT), 1995.

C Scientific books (monographs)

Scientific monographs or parts of publication series edited or translated by the author

115. Miika Toivanen, Kai Puolamäki, Kristian Lukander, Jukka Häkkinen, Jenni Radun. Inferring user action with mobile gaze tracking. In Adjunct Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, 1026-1028, 2016. https://doi.org/10.1145/2957265.2965016 

116. [highly cited][2] Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis, and Florian Mansmann, editors. Mastering the Information Age Solving Problems with Visual Analytics, chapter Data Mining by Kai Puolamäki et al., pages 39–56. Eurographics Association, 2010. http://www.vismaster.eu/book/ 

117. [highly cited] Kai Puolamäki and Alessio Bertone. Introduction to special issue on visual analytics and knowledge discovery. SIGKDD Explorations, 11(2):3–4, 2009. http://www.hiit.fi/vakd09/si.html 

118. Kai Puolamäki, editor. Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery, 2009. https://doi.org/10.1145/1562849 

119. Kai Puolamäki and Samuel Kaski, editors. Proceedings of the NIPS 2005 Workshop on Machine Learning for Implicit Feedback and User Modeling, 2006. http://research.ics.aalto.fi/events/inips2005/inips2005proceedings.pdf 

120. Kai Puolamäki and Leila Koivisto, editors. Biennial report 2002–2003. Laboratory of Computer and Information Science, 2004. http://www.cis.hut.fi/research/reports/biennial02-03/ 

121. Kai Puolamäki and Leila Koivisto, editors. Biennial report 2000–2001. Laboratory of Computer and Information Science, 2002. http://www.cis.hut.fi/research/reports/biennial00-01/ 

D Publications intended for professional communities

Teaching materials

122. Kai Puolamäki. T-61.3050: Machine learning: Basic principles. Available for download at http://www.cis.hut.fi/Opinnot/T-61.3050/2007/lectures, 2007. Lecturing material.

Research agendas

123. Petri Myllymäki, Jukka Ahtikari, Kai Puolamäki, Christer Carlsson, Sami Sahala, Rauno Saarnio, and Pentti Kurki. Strategic Research Agenda for Data to Intelligence (D2I). TiViT, 2011. http://www.datatointelligence.fi/file_attachment/get/D2I_SRA.pdf?attachment_id=6 

E Publications intended for the general public

Expert statements for the parliament

124. Kai Puolamäki. Lausunto eduskunnan hallintovaliokunnalle sähköisen viestinnän tietosuojalaista, 2003. http://www.effi.org/julkaisut/lausunnot/svt-2003-11-28.html 

125. Kai Puolamäki. Lausunto eduskunnan perustuslakivaliokunnalle laista sananvapauden käyttämisestä joukkoviestinnässä, 2002. http://www.effi.org/sananvapaus/lausunto-2002-10-16.html 

Expert statements for the government

126. Kai Puolamäki. Lausunto liikenne- ja viestintäministeriölle komission roskapostia koskevasta tiedonannosta, 2004. http://www.effi.org/julkaisut/lausunnot/lvm-2004-02-06.html 

127. Kai Puolamäki. Lausunto opetusministeriölle opetusministeriön luonnoksesta tekijänoikeuslaiksi, 2003. http://www.effi.org/tekijanoikeus/laki/effi-2003-09-05.pdf 

128. Kai Puolamäki. Lausunto liikenne- ja viestintäministeriölle hallituksen toisesta esitysluonnoksesta sähköisen viestinnän tietosuojalaiksi, 2003. http://www.effi.org/julkaisut/lausunnot/svt-2003-05-06.html 

129. Kai Puolamäki. Lausunto liikenne- ja viestintäministeriölle hallituksen esitysluonnoksesta sähköisen viestinnän tietosuojalaiksi, 2003. http://www.effi.org/julkaisut/lausunnot/svt-2003-02-07.html 

130. Kai Puolamäki. Lausunto sisäasianministeriölle puuttumisesta Internetin rikolliseen sisältöön. In Internetissä julkaistavan rikollisen materiaalin rajoittamista selvittäneen työryhmän raportti, volume 2/2003 of Poliisiosaston julkaisut, pages 36–41. Sisäasasiainministeriö, 2003. http://www.poliisi.fi/intermin/biblio.nsf/vwByseriesPol/CEA68036D0B8E2C9C2256CAF0030B83A 

G Theses

131. Kai Puolamäki. Breaking of R-Parity and Supersymmetry in Supersymmetric Models. PhD thesis, University of Helsinki, 2001. http://ethesis.helsinki.fi/julkaisut/eri/fysii/vk/puolamaki/ 

132. Kai Puolamäki. On spontaneously broken R-parity. Master's thesis, University of Helsinki, 1996.

I Audiovisual material, ICT software

133. Laila Melkas, Jarmo Mäkelä, Suyog Chandramouli, Ivan Mammarella, Tuomo Nieminen, Kai Puolamäki, Rafael Savvides. Interactive Causal Structure Discovery with Hyytiälä measurements (experiment code and data). Zenodo, 2022. https://doi.org/10.5281/ZENODO.6451931 

134. Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, Kai Puolamäki. Datasets of Air Pollutants on Boulevard Type Streets and Software to Replicate Large-Eddy Simulations of Air Pollutant Concentrations Along Boulevard-Type Streets. Zenodo, 2020. https://doi.org/10.5281/ZENODO.3999301 

135. Kai Puolamäki. CORAND library. Available for download under an open source license at https://github.com/edahelsinki/corand, 2019. Computer program.

136. Kai Puolamäki. cyclesampler. Available for download under an open source license at https://github.com/edahelsinki/cyclesampler, 2019. Computer program.

137. Kai Puolamäki. Corand library. 2019.  https://github.com/edahelsinki/corand 

138. Kai Puolamäki. sideR library. 2019. https://github.com/edahelsinki/sideR 

139. Kai Puolamäki. Cyclesampler library. 2019. https://github.com/edahelsinki/cyclesampler 

140. Kai Puolamäki. sideR - subjective and interactive visual data exploration in R. Available for download under an open source license at https://github.com/edahelsinki/sideR, 2017. Computer program.

 

141. Kai Puolamäki. Software for seriation in paleontological data using Markov chain Monte Carlo methods. Available for download under an open source license at http://www.cis.hut.fi/projects/patdis/paleo/, 2006. Computer program.

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[1] https://scholar.google.com/citations?user=3Z9pgDAAAAAJ 

[2] The citation count is for the whole book.