's List of Publications

Articles in International Refereed Scientific Journals

[1] Mehmet Gönen, Barbara A. Weir, Glenn S. Cowley, Francisca Vazquez, Yuanfang Guan, Alok Jaiswal, Masayuki Karasuyama, Vladislav Uzunangelov, Tao Wang, Aviad Tsherniak, Sara Howell, Daniel Marbach, Bruce Hoff, Thea C. Norman, Antti Airola, Adrian Bivol, Kerstin Bunte, Daniel Carlin, Sahil Chopra, Alden Deran, Kyle Ellrott, Peddinti Gopalacharyulu, Kiley Graim, Samuel Kaski, Suleiman A. Khan, Yulia Newton, Sam Ng, Tapio Pahikkala, Evan Paull, Artem Sokolov, Hao Tang, Jing Tang, Krister Wennerberg, Yang Xie, Xiaowei Zhan, Fan Zhu, Tero Aittokallio, Hiroshi Mamitsuka, Joshua M. Stuart, Jesse S. Boehm, Dave A. Root, Guanghua Xiao, Gustavo Stolovitzky, William C. Hahn, and Adam A. Margolin. A community challenge for inferring genetic predictors of gene essentialities through analysis of a functional screen of cancer cell lines. Cell Systems, 2017. In Press. [ bib | DOI | http ]
[2] Antti Airola and Tapio Pahikkala. Fast kronecker product kernel methods via generalized vec trick. IEEE Transactions on Neural Networks and Learning Systems, 2017. In press. [ bib | DOI | arXiv ]
[3] Anja Eberl, Saara Huoponen, Tapio Pahikkala, Marja Blom, Perttu Arkkila, and Taina Sipponen. Switching maintenance infliximab therapy to biosimilar infliximab in inflammatory bowel disease patients. Scandinavian Journal of Gastroenterology, 52(12):1348--1353, 2017. [ bib | DOI | http ]
[4] Anna Cichonska, Balaguru Ravikumar, Elina Parri, Sanna Timonen, Tapio Pahikkala, Antti Airola, Krister Wennerberg, Juho Rousu, and Tero Aittokallio. Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. PLOS Computational Biology, 13(8):1--28, 08 2017. [ bib | DOI | http ]
[5] Pekka Naula, Antti Airola, Sari Pihlasalo, Ileana Montoya Perez, Tapio Salakoski, and Tapio Pahikkala. Assessment of metal ion concentration in water with structured feature selection. Chemosphere, 185:1063--1071, October 2017. [ bib | DOI | http ]
[6] Markus Viljanen, Antti Airola, Jukka Heikkonen, and Tapio Pahikkala. Playtime measurement with survival analysis. IEEE Transactions on Computational Intelligence and AI in Games, 2017. In press. [ bib | DOI ]
[7] Justin Guinney, Tao Wang, Teemu D Laajala, Kimberly Kanigel Winner, J Christopher Bare, Elias Chaibub Neto, Suleiman A Khan, Gopal Peddinti, Antti Airola, Tapio Pahikkala, Tuomas Mirtti, Thomas Yu, Brian M Bot, Liji Shen, Kald Abdallah, Thea Norman, Stephen Friend, Gustavo Stolovitzky, Howard Soule, Christopher J. Sweeney, Charles J Ryan, Howard I. Scher, Oliver Sartor, Yang Xie, Tero Aittokallio, Fang Liz Zhou, and James C Costello. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data. The Lancet Oncology, 18(1):132--142, 2017. [ bib | DOI | http ]
[8] Jonne Pohjankukka, Tapio Pahikkala, Paavo Nevalainen, and Jukka Heikkonen. Estimating the prediction performance of spatial models via spatial k-fold cross validation. International Journal of Geographical Information Science, 31(10):2001--2019, 2017. [ bib | DOI | http ]
[9] Milla Högmander, Catherine J. Paul, Sandy Chan, Elina Hokkanen, Ville Eskonen, Tapio Pahikkala, and Sari Pihlasalo. Luminometric label array for counting and differentiation of bacteria. Analytical Chemistry, 89(5):3208--3216, 2017. [ bib | DOI | http ]
[10] Harri Merisaari, Parisa Movahedi, Ileana Montoya Perez, Jussi Toivonen, Marko Pesola, Pekka Taimen, Peter Boström, Aida Kiviniemi, Tapio Pahikkala, Hannu J. Aronen, and Ivan Jambor. Fitting methods for intravoxel incoherent motion imaging of prostate cancer on region of interest level: repeatability and Gleason score prediction. Magnetic Resonance in Medicine, 77(3):1249--1264, 2017. [ bib | DOI | http ]
[11] Iman Azimi, Arman Anzanpour, Amir M. Rahmani, Tapio Pahikkala, Marco Levorato, Pasi Liljeberg, and Nikil Dutt. HiCH: Hierarchical fog-assisted computing architecture for healthcare IoT. ACM Transactions on Embedded Computing Systems, 16(5s):174:1--174:20, September 2017. [ bib | DOI | http ]
[12] Ville Taajamaa, Anne-Maarit Majanoja, Diana Bairaktarova, Antti Airola, Tapio Pahikkala, and Erkki Sutinen. How engineers perceive the importance of ethics in finland. European Journal of Engineering Education, 2017. Accepted for publication. [ bib | DOI | http ]
[13] Tapio Pahikkala and Antti Airola. Rlscore: Regularized least-squares learners. Journal of Machine Learning Research, 17(221):1--5, 2016. [ bib | .html ]
[14] Kristiina Santalahti, Mikael Maksimow, Antti Airola, Tapio Pahikkala, Nina Hutri-Kähönen, Sirpa Jalkanen, Olli T. Raitakari, and Marko Salmi. Circulating cytokines predict the development of insulin resistance in a prospective finnish population cohort. The Journal of Clinical Endocrinology & Metabolism, 101(9):3361--3369, 2016. [ bib | DOI | http ]
[15] Sari Pihlasalo, Ileana Montoya Perez, Niklas Hollo, Elina Hokkanen, Tapio Pahikkala, and Harri Härmä. Luminometric label array for quantification and identification of metal ions. Analytical Chemistry, 88(10):5271--5280, 2016. [ bib | DOI | http ]
[16] Jonne Pohjankukka, Henri Riihimäki, Paavo Nevalainen, Tapio Pahikkala, Jari Ala-Ilomäki, Eija Hyvönen, Jari Varjo, and Jukka Heikkonen. Predictability of boreal forest soil bearing capacity by machine learning. Journal of Terramechanics, 68:1--8, 2016. [ bib | DOI | http ]
[17] Paavo Nevalainen, Maarit Middleton, Raimo Sutinen, Jukka Heikkonen, and Tapio Pahikkala. Detecting terrain stoniness from airborne laser scanning data. Remote Sensing, 8(9):720, 2016. [ bib | DOI | http ]
[18] Fahimeh Farahnakian, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, Trung Hieu Nguyen, and Hannu Tenhunen. Energy-aware VM consolidation in cloud data centers using utilization prediction model. IEEE Transactions on Cloud Computing, 2016. Accepted for publication. [ bib | DOI ]
[19] Hans Moen, Laura-Maria Murtola, Juho Heimonen, Antti Airola, Tapio Pahikkala, Tapio Salakoski, and Sanna Salanterä. Comparison of automatic summarisation methods for clinical free text notes. Artificial Intelligence in Medicine, 67:25--37, February 2016. [ bib | DOI | http ]
[20] Ville Taajamaa, Mona Eskandari, Barbara A. Karanian, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. O-CDIO: Emphasizing design thinking in CDIO engineering cycle. International Journal of Engineering Education, 32(3):1530--1539, 2016. [ bib ]
[21] Tapio Pahikkala, Kim Kari, Heta Mattila, Anna Lepistö, Jukka Teuhola, Olli S. Nevalainen, and Esa Tyystjärvi. Classification of plant species from images of overlapping leaves. Computers and Electronics in Agriculture, 118:186--192, 2015. [ bib | DOI | http ]
[22] Harri Merisaari, Jussi Toivonen, Marko Pesola, Pekka Taimen, Peter Boström, Tapio Pahikkala, Hannu J. Aronen, and Ivan Jambor. Diffusion weighted imaging of prostate cancer: Effect of b-value distribution on repeatability and cancer characterization. Magnetic Resonance Imaging, 33(10):1212--1218, 2015. [ bib | DOI | http ]
[23] Jussi Toivonen, Harri Merisaari, Marko Pesola, Pekka Taimen, Peter Boström, Tapio Pahikkala, Hannu J. Aronen, and Ivan Jambor. Mathematical models for diffusion weighted imaging of prostate cancer using b-values up to 2000 s/mm2: correlation with gleason score and repeatability of region of interest analysis. Magnetic Resonance in Medicine, 74(4):1116--1124, October 2015. [ bib | DOI | http ]
[24] Fahimeh Farahnakian, Adnan Ashraf, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, Ivan Porres, and Hannu Tenhunen. Using ant colony system to consolidate VMs for green cloud computing. IEEE Transactions on Services Computing, 8(2):187--198, March 2015. [ bib ]
[25] Tapio Pahikkala, Antti Airola, Sami Pietilä, Sushil Shakyawar, Agnieszka Szwajda, Jing Tang, and Tero Aittokallio. Toward more realistic drug-target interaction predictions. Briefings in Bioinformatics, 16(2):325--337, 2015. [ bib | DOI | Data available | http ]
[26] Frans Vainio, Tapio Pahikkala, Mika Johnsson, Olli S. Nevalainen, and Timo Knuutila. Estimating the production time of a PCB assembly job without solving the optimised machine control. International Journal of Computer Integrated Manufacturing, 28(8):823--835, 2015. [ bib | DOI | http ]
[27] Sebastian Okser, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Samuli Ripatti, and Tero Aittokallio. Regularized machine learning in the genetic prediction of complex traits. PLOS Genetics, 10(11):e1004754, November 2014. [ bib | DOI | http ]
[28] Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, and Willem Waegeman. Identification of functionally related enzymes by learning-to-rank methods. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(6):1157--1169, 2014. [ bib | DOI | arXiv | http ]
[29] Elina Kontio, Antti Airola, Tapio Pahikkala, Heljä Lundgrén-Laine, Kristiina Junttila, Heikki Korvenranta, Tapio Salakoski, and Sanna Salanterä. Predicting patient acuity from electronic patient records. Journal of Biomedical Informatics, 51(0):35--40, October 2014. [ bib | DOI | http ]
[30] Pekka Naula, Antti Airola, Tapio Salakoski, and Tapio Pahikkala. Multi-label learning under feature extraction budgets. Pattern Recognition Letters, 40:56--65, April 2014. [ bib | DOI | http ]
[31] Fabian Gieseke, Antti Airola, Tapio Pahikkala, and Oliver Kramer. Fast and simple gradient-based optimization for semi-supervised support vector machines. Neurocomputing, 123:23--32, January 2014. [ bib | DOI | http ]
[32] Tapio Pahikkala, Antti Airola, Fabian Gieseke, and Oliver Kramer. On unsupervised training of multi-class regularized least-squares classifiers. Journal of Computer Science and Technology, 29(1):90--104, January 2014. [ bib | DOI | http ]
[33] Tapio Pahikkala, Antti Airola, Michiel Stock, Bernard De Baets, and Willem Waegeman. Efficient regularized least-squares algorithms for conditional ranking on relational data. Machine Learning, 93(2-3):321--356, 2013. [ bib | DOI | http | .pdf ]
[34] Heta Mattila, Pertti Valli, Tapio Pahikkala, Jukka Teuhola, Olli S. Nevalainen, and Esa Tyystjärvi. Comparison of chlorophyll fluorescence curves and texture analysis for automatic plant identification. Precision Agriculture, 14(6):621--636, December 2013. [ bib | DOI | http ]
[35] Sebastian Okser, Tapio Pahikkala, and Tero Aittokallio. Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives. BioData Mining, 6(1):5, 2013. [ bib | DOI | http ]
[36] Willem Waegeman, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Michiel Stock, and Bernard De Baets. A kernel-based framework for learning graded relations from data. IEEE Transactions on Fuzzy Systems, 20(6):1090--1101, December 2012. [ bib | DOI | http | .pdf ]
[37] Tapio Pahikkala, Hanna Suominen, and Jorma Boberg. Efficient cross-validation for kernelized least-squares regression with sparse basis expansions. Machine Learning, 87(3):381--407, June 2012. [ bib | DOI | http | .pdf ]
[38] Tapio Pahikkala, Sebastian Okser, Antti Airola, Tapio Salakoski, and Tero Aittokallio. Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations. Algorithms for Molecular Biology, 7(1):11, 2012. [ bib | DOI | http ]
[39] Fabian Gieseke, Oliver Kramer, Antti Airola, and Tapio Pahikkala. Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification. Evolutionary Intelligence, 5(3):189--205, September 2012. [ bib | DOI | http | .pdf ]
[40] Tapio Pahikkala, Antti Airola, Thomas Canhao Xu, Pasi Liljeberg, Hannu Tenhunen, and Tapio Salakoski. Parallelized online regularized least-squares for adaptive embedded systems. International Journal of Embedded and Real-Time Communication Systems, 3(2):73--91, April 2012. [ bib | DOI ]
[41] Jari Björne, Juho Heimonen, Filip Ginter, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Extracting contextualized complex biological events with rich graph-based feature sets. Computational Intelligence, 27(4):541--557, November 2011. [ bib ]
[42] Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Training linear ranking SVMs in linearithmic time using red-black trees. Pattern Recognition Letters, 32(9):1328--1336, July 2011. [ bib | DOI | http ]
[43] Antti Airola, Tapio Pahikkala, Willem Waegeman, Bernard De Baets, and Tapio Salakoski. An experimental comparison of cross-validation techniques for estimating the area under the ROC curve. Computational Statistics & Data Analysis, 55(4):1828--1844, April 2011. [ bib | DOI | http ]
[44] Antti Airola, Tapio Pahikkala, and Tapio Salakoski. On learning and cross-validation with decomposed Nyström approximation of kernel matrix. Neural Processing Letters, 33(1):17--30, February 2011. [ bib | DOI | http ]
[45] Tapio Pahikkala, Willem Waegeman, Evgeni Tsivtsivadze, Tapio Salakoski, and Bernard De Baets. Learning intransitive reciprocal relations with kernel methods. European Journal of Operational Research, 206(3):676--685, November 2010. [ bib | DOI | http ]
[46] Tapio Pahikkala, Evgeni Tsivtsivadze, Antti Airola, Jouni Järvinen, and Jorma Boberg. An efficient algorithm for learning to rank from preference graphs. Machine Learning, 75(1):129--165, April 2009. [ bib | DOI | http | .pdf ]
[47] Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Matrix representations, linear transformations, and kernels for disambiguation in natural language. Machine Learning, 74(2):133--158, February 2009. [ bib | DOI | http | .pdf ]
[48] Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Locality kernels for sequential data and their applications to parse ranking. Applied Intelligence, 31(1):81--88, 2009. [ bib ]
[49] Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, and Tapio Salakoski. All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning. BMC Bioinformatics, 9 Suppl 11, 2008. [ bib ]
[50] Tero Aittokallio, Jani S. Malminen, Tapio Pahikkala, Olli Polo, and Olli Nevalainen. Inspiratory flow shape clustering: An automated method to monitor upper airway performance during sleep. Computer Methods and Programs in Biomedicine, 85(1):8--18, Jan 2007. [ bib | DOI | http ]
[51] Marketta Hiissa, Tapio Pahikkala, Hanna Suominen, Tuija Lehtikunnas, Barbro Back, Helena Karsten, Sanna Salanterä, and Tapio Salakoski. Towards automated classification of intensive care nursing narratives. International Journal of Medical Informatics, 76(Supplement 3):S362--S368, December 2007. [ bib | DOI ]
[52] Heidi Vähämaa, Pekka Ojala, Tapio Pahikkala, Olli S. Nevalainen, Riitta Lahesmaa, and Tero Aittokallio. Computer-assisted identification of multi-trace electrophoretic patterns in differential display experiments. Electrophoresis, 28(6):879--893, 2007. [ bib | DOI | http ]
[53] Sampo Pyysalo, Filip Ginter, Tapio Pahikkala, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Evaluation of two dependency parsers on biomedical corpus targeted at protein-protein interactions. International Journal of Medical Informatics, 75(6):430--442, June 2006. [ bib ]
[54] Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Contextual weighting for support vector machines in literature mining: An application to gene versus protein name disambiguation. BMC Bioinformatics, 6(1):157, 2005. [ bib | DOI ]
[55] Tero Aittokallio, Tapio Pahikkala, Pekka Ojala, Timo J. Nevalainen, and Olli Nevalainen. Electrophoretic signal comparison applied to mRNA differential display analysis. BioTechniques, 34(1):116--122, Jan 2003. [ bib | .pdf ]

Co-Edited Conference Proceedings

[56] Sasu Tarkoma, Joni-Kristian Kämäräinen, and Tapio Pahikkala, editors. The Federated Computer Science Event, Helsinki, Finland, 2012. Unigrafia Oy. [ bib | .pdf ]
[57] Tapio Pahikkala, Jaakko Väyrynen, Jukka Kortela, and Antti Airola, editors. Proceedings of the 14th Finnish Artificial Intelligence Conference, STeP 2010, number 25 in Publications of the Finnish Artificial Intelligence Society, Espoo, Finland, 2010. Aalto-Print. [ bib ]
[58] Tapio Salakoski, Filip Ginter, Sampo Pyysalo, and Tapio Pahikkala, editors. Proceedings of the Fifth International Conference on Natural Language Processing (FinTAL), volume 4139 of Lecture Notes in Artificial Intelligence, Berlin, Heidelberg, August 2006. Springer. [ bib | DOI ]

Articles in International Refereed Scientific Edited Volumes and Conference Proceedings

[59] Markus Viljanen, Antti Airola, Tapio Pahikkala, and Jukka Heikkonen. User activity decay in mobile games determined by simple differential equations? In Kostas Karpouzis, Gillian Smith, Georgios N. Yannakakis, and Tommy Thompson, editors, The annual IEEE Conference on Computational Intelligence and Games (IEEE CIG), pages 126--133. IEEE, 2016. [ bib | DOI ]
[60] Markus Viljanen, Antti Airola, Tapio Pahikkala, and Jukka Heikkonen. Modelling user retention in mobile games. In Kostas Karpouzis, Gillian Smith, Georgios N. Yannakakis, and Tommy Thompson, editors, The annual IEEE Conference on Computational Intelligence and Games (IEEE CIG), pages 62--69. IEEE, 2016. [ bib | DOI ]
[61] Ileana Montoya Perez, Jussi Toivonen, Parisa Movahedi, Harri Merisaari, Marko Pesola, Pekka Taimen, Peter J. Boström, Aida Kiviniemi, Hannu J. Aronen, Tapio Pahikkala, and Ivan Jambor. Diffusion weighted imaging of prostate cancer: Prediction of cancer using texture features from parametric maps of the monoexponential and kurtosis functions. In Miguel Bordallo López, Abdenour Hadid, and Matti Pietikäinen, editors, The 6th International Conference on Image Processing Theory, Tools and Applications (IPTA 2016), December 2016. [ bib | DOI ]
[62] Fahimeh Farahnakian, Rami Bahsoon, Pasi Liljeberg, and Tapio Pahikkala. Self-adaptive resource management system in iaas clouds. In Ian Foster and Nimish Radia, editors, IEEE International Conference on Cloud Computing (CLOUD 2016), pages 553--560. IEEE, June 2016. [ bib | DOI ]
[63] Fabian Gieseke, Tapio Pahikkala, and Tom Heskes. Batch steepest-descent-mildest-ascent for interactive maximum margin clustering. In Elisa Fromont, Tijl De Bie, and Matthijs van Leeuwen, editors, The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015), volume 9385 of Lecture Notes in Computer Science, pages 95--107. Springer International Publishing, 2015. [ bib | DOI | http ]
[64] Paavo Nevalainen, Maarit Middleton, Ilkka Kaate, Tapio Pahikkala, Raimo Sutinen, and Jukka Heikkonen. Detecting stony areas based on ground surface curvature distribution. In Rachid Jennane, editor, The 5th International Conference on Image Processing Theory, Tools and Applications (IPTA 2015), pages 581--587, November 2015. [ bib | DOI ]
[65] Mohammad Fattah, Antti Airola, Rachata Ausavarungnirun, Nima Mirzaei, Pasi Liljeberg, Juha Plosila, Siamak Mohammadi, Tapio Pahikkala, Onur Mutlu, and Hannu Tenhunen. A low-overhead, fully-distributed, guaranteed-delivery routing algorithm for faulty network-on-chips. In André Ivanov, Diana Marculescu, Partha Pratim Pande, José Flich, and Karthik Pattabiraman, editors, Proceedings of the 9th International Symposium on Networks-on-Chip (NOCS'15), pages 18:1--18:8. ACM, September 2015. [ bib | DOI | http ]
[66] Pekka Naula, Antti Airola, Tapio Salakoski, and Tapio Pahikkala. Learning low cost multi-target models by enforcing sparsity. In Moonis Ali, Young Sig Kwon, Chang-Hwan Lee, Juntae Kim, and Yongdai Kim, editors, The 28th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2015), Lecture Notes in Computer Science, pages 252--261. Springer, 2015. [ bib | DOI | http ]
[67] Thomas Canhao Xu, Jonne Pohjankukka, Paavo Nevalainen, Ville Leppänen, and Tapio Pahikkala. Parallel applications and on-chip traffic distributions: Observation, implication and modelling. In Pascal Lorenz and Leszek A. Maciaszek, editors, Proceedings of the 10th International Conference on Software Engineering and Applications (ICSOFT-EA), pages 443--449, July 2015. [ bib | DOI | http ]
[68] Fahimeh Farahnakian, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, and Hannu Tenhunen. Utilization prediction aware VM consolidation approach for green cloud computing. In Calton Pu and Ajay Mohindra, editors, 8th IEEE International Conference on Cloud Computing (CLOUD 2015), pages 381--388. IEEE, June 2015. [ bib ]
[69] Parisa Movahedi, Paavo Nevalainen, Markus Viljanen, and Tapio Pahikkala. Fast regularized least squares and k-means clustering method for intrusion detection systems. In Maria De Marsico, Mário A. T. Figueiredo, and Ana L. N. Fred, editors, Proceedings of the 4th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2015), pages 264--269. SciTePress, 2015. [ bib | DOI ]
[70] Tapio Pahikkala, Michiel Stock, Antti Airola, Tero Aittokallio, Bernard De Baets, and Willem Waegeman. A two-step learning approach for solving full and almost full cold start problems in dyadic prediction. In Toon Calders, Floriana Esposito, Eyke Hüllermeier, and Rosa Meo, editors, Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2014), volume 8725 of Lecture Notes in Computer Science, pages 517--532. Springer, 2014. [ bib | DOI ]
[71] Tapio Pahikkala. Fast gradient computation for learning with tensor product kernels and sparse training labels. In Pasi Fränti, Gavin Brown, Marco Loog, Francisco Escolano, and Marcello Pelillo, editors, Structural, Syntactic, and Statistical Pattern Recognition (S+SSPR 2014), volume 8621 of Lecture Notes in Computer Science, pages 123--132. Springer, 2014. [ bib | DOI | Preprint ]
[72] Juho Heimonen, Tapio Salakoski, and Tapio Pahikkala. Properties of object-level cross-validation schemes for symmetric pair-input data. In Pasi Fränti, Gavin Brown, Marco Loog, Francisco Escolano, and Marcello Pelillo, editors, Structural, Syntactic, and Statistical Pattern Recognition (S+SSPR 2014), volume 8621 of Lecture Notes in Computer Science, pages 384--393. Springer, 2014. [ bib | DOI ]
[73] Jonne Pohjankukka, Paavo Nevalainen, Tapio Pahikkala, Eija Hyvönen, Raimo Sutinen, Pekka Hänninen, and Jukka Heikkonen. Arctic soil hydraulic conductivity and soil type recognition based on aerial gamma-ray spectroscopy and topographical data. In Magnus Borga, Anders Heyden, Denis Laurendeau, Michael Felsberg, and Kim Boyer, editors, Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014), pages 1822--1827. IEEE, Aug 2014. [ bib | DOI ]
[74] Jonne Pohjankukka, Paavo Nevalainen, Tapio Pahikkala, Eija Hyvönen, Pekka Hänninen, Raimo Sutinen, Jari Ala-Ilomäki, and Jukka Heikkonen. Predicting water permeability of the soil based on open data. In Lazaros Iliadis, Ilias Maglogiannis, and Harris Papadopoulos, editors, Proceedings of the 10th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2014), volume 436 of IFIP Advances in Information and Communication Technology, pages 436--446. Springer, 2014. [ bib | DOI ]
[75] Hans Moen, Juho Heimonen, Laura-Maria Murtola, Antti Airola, Tapio Pahikkala, Virpi Terävä, Riitta Danielsson-Ojala, Tapio Salakoski, and Sanna Salanterä. On evaluation of automatically generated clinical discharge summaries. In Ellen A.A. Jaatun, Elizabeth Brooks, Kirsti Berntsen, Heidi Gilstad, and Martin Gilje Jaatun, editors, Proceedings of the 2nd European Workshop on Practical Aspects of Health Informatics (PAHI 2014), volume 1251 of CEUR Workshop Proceedings, pages 101--114. CEUR-WS.org, 2014. [ bib ]
[76] Thomas Canhao Xu, Jussi Toivonen, Tapio Pahikkala, and Ville Leppänen. Bdmap: A heuristic application mapping algorithm for the big data era. In Proceedings of the 14th IEEE International Conference on Scalable Computing and Communications (ScalCom-2014), pages 821--828. IEEE, 2014. [ bib ]
[77] Fahimeh Farahnakian, Pasi Liljeberg, Tapio Pahikkala, Juha Plosila, and Hannu Tenhunen. Hierarchical vm management architecture for cloud data centers. In The 6th International Conference on Cloud Computing (CloudCom 2014), pages 306--311, December 2014. [ bib ]
[78] Fahimeh Farahnakian, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, and Hannu Tenhunen. Multi-agent based architecture for dynamic vm consolidation in cloud data centers. In 40th Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2014), pages 111--118, August 2014. [ bib ]
[79] Fahimeh Farahnakian, Adnan Ashraf, Pasi Liljeberg, Tapio Pahikkala, Juha Plosila, Ivan Porres, and Hannu Tenhunen. Energy-aware dynamic VM consolidation in cloud data centers using ant colony system. In Alan Sussman, Liana L. Fong, Stephen S. Yau, Ephraim Feig, and Carl Kesselman, editors, IEEE International Conference on Cloud Computing (CLOUD 2014), pages 104--111. IEEE, June 2014. [ bib ]
[80] Fabian Gieseke, Tapio Pahikkala, and Christian Igel. Polynomial runtime bounds for fixed-rank unsupervised least-squares classification. In Cheng Soon Ong and Tu Bao Ho, editors, Proceedings of the 5th Asian Conference on Machine Learning (ACML 2013), volume 29 of JMLR Workshop and Conference Proceedings, pages 62--71. JMLR, November 2013. [ bib | .pdf ]
[81] Thomas Canhao Xu, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, and Hannu Tenhunen. Optimized multicore architectures for data parallel fast fourier transform. In Proceedings of the 14th International Conference on Computer Systems and Technologies, CompSysTech '13, pages 75--82, New York, NY, USA, 2013. The Association for Computing Machinery (ACM). [ bib | DOI | http ]
[82] Jari Björne, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Analyzing the japanese toxicogenomics project dataset with svm and rls classifiers. In 13th Annual International Conference on Critical Assessment of Massive Data Analysis (CAMDA 2013), 2013. [ bib ]
[83] Sebastian Okser, Antti Airola, Tapio Salakoski, Tero Aittokallio, and Tapio Pahikkala. Parallel feature selection for regularized least-squares. In Pekka Manninen and Per Öster, editors, Proceedings of the 11th international conference on Applied Parallel and Scientific Computing (PARA 2012), Revised Selected Papers, volume 7782 of Lecture Notes in Computer Science, pages 280--294. Springer, 2013. [ bib | DOI ]
[84] Antti Airola, Tapio Pahikkala, Heljä Lundgrén-Laine, Anne Santalahti, Sanna Salanterä, and Tapio Salakoski. A machine learning approach towards early detection of frequent health care users. In Hanna Suominen, editor, The 4th International Louhi Workshop on Health Document Text Mining and Information Analysis (Louhi 2013), 2013. [ bib ]
[85] Fahimeh Farahnakian, Tapio Pahikkala, Pasi Liljeberg, and Juha Plosila. Energy aware consolidation algorithm based on k-nearest neighbor regression for cloud data centers. In IEEE/ACM Utility and Cloud Computing conference (UCC), pages 256--259. IEEE, December 2013. [ bib ]
[86] Tapio Pahikkala, Antti Airola, Fabian Gieseke, and Oliver Kramer. Unsupervised multi-class regularized least-squares classification. In Mohammed J. Zaki, Arno Siebes, Jeffrey Xu Yu, Bart Goethals, Geoff Webb, and Xindong Wu, editors, The 12th IEEE International Conference on Data Mining (ICDM 2012), pages 585--594. IEEE Computer Society, December 2012. [ bib | DOI | .pdf ]
[87] Michiel Stock, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Bernard De Baets, and Willem Waegeman. Learning monadic and dyadic relations: Three case studies in systems biology. In Oliver Ray and Katsumi Inoue, editors, Proceedings of the ECML/PKDD 2012 Workshop on Learning and Discovery in Symbolic Systems Biology, pages 74--84, September 2012. [ bib ]
[88] Fabian Gieseke, Antti Airola, Tapio Pahikkala, and Oliver Kramer. Sparse quasi-newton optimization for semi-supervised support vector machines. In Pedro Latorre Carmona, J. Salvador Sánchez, and Ana L. N. Fred, editors, Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods (ICPRAM), pages 45--54. SciTePress, 2012. [ bib ]
[89] Thomas Canhao Xu, Tapio Pahikkala, Antti Airola, Pasi Liljeberg, Juha Plosila, Tapio Salakoski, and Hannu Tenhunen. Implementation and analysis of block dense matrix decomposition on network-on-chips. In Geyong Min, Jia Hu, Lei (Chris) Liu, Laurence T. Yang, Seetharami Seelam, and Laurent Lefevre, editors, The 14th IEEE International Conference on High Performance Computing and Communications (HPCC-2012), pages 516--523. IEEE Computer Society, June 2012. [ bib | DOI ]
[90] Willem Waegeman, Tapio Pahikkala, Antti Airola, Tapio Salakoski, and Bernard De Baets. Learning valued relations from data. In Pedro Melo-Pinto, Pedro Couto, Carlos Serôdio, János Fodor, and Bernard De Baets, editors, Eurofuse 2011, volume 107 of Advances in Intelligent and Soft Computing, pages 257--268. Springer, 2012. [ bib | DOI | http ]
[91] Pekka Naula, Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Greedy regularized least-squares for multi-task learning. In Myra Spiliopoulou, Haixun Wang, Diane Cook, Jian Pei, Wei Wang, Osmar Zaïane, and Xindong Wu, editors, 11th IEEE International Conference on Data Mining Workshops (ICDMW'11), pages 527--533. IEEE Computer Society, December 2011. [ bib | DOI ]
[92] Sebastian Okser, Tapio Pahikkala, Antti Airola, Tero Aittokallio, and Tapio Salakoski. Fast and parallelized greedy forward selection of genetic variants in genome-wide association studies. In Yidong Chen, Yufei Huang, and Edward Dougherty, editors, IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS'11), pages 214--217. IEEE Signal Processing Society, December 2011. [ bib | DOI ]
[93] Fabian Gieseke, Oliver Kramer, Antti Airola, and Tapio Pahikkala. Speedy local search for semi-supervised regularized least-squares. In Joscha Bach and Stefan Edelkamp, editors, KI 2011: Advances in Artificial Intelligence, volume 7006 of Lecture Notes in Computer Science, pages 87--98. Springer, 2011. [ bib | DOI | http ]
[94] Jari Björne, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Drug-drug interaction extraction with SVM and RLS classifiers. In Isabel Segura-Bedmar, Paloma Martinez, and Daniel Sanchez-Cisneros, editors, Proceedings of the 1st Challenge Task on Drug-Drug Interaction Extraction 2011, volume 761 of CEUR Workshop Proceedings. CEUR-WS.org, September 2011. [ bib ]
[95] Antti Airola, Tapio Pahikkala, and Tapio Salakoski. An improved training algorithm for the linear ranking support vector machine. In Timo Honkela, Wlodzislaw Duch, Mark Girolami, and Samuel Kaski, editors, Artificial Neural Networks and Machine Learning -- ICANN 2011, volume 6791 of Lecture Notes in Computer Science, pages 134--141. Springer, June 2011. [ bib ]
[96] Pekka Naula, Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Learning multi-label predictors under sparsity budget. In Anders Kofod-Petersen, Fredrik Heintz, and Helge Langseth, editors, Eleventh Scandinavian Conference on Artificial Intelligence, SCAI 2011, volume 227 of Frontiers in Artificial Intelligence and Applications, pages 30--39. IOS Press, May 2011. [ bib ]
[97] Tapio Pahikkala, Antti Airola, Thomas Canhao Xu, Pasi Liljeberg, Hannu Tenhunen, and Tapio Salakoski. A parallel online regularized least-squares machine learning algorithm for future multi-core processors. In César Benavente-Peces and Joaquim Filipe, editors, Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2011), pages 590--599. SciTePress, March 2011. [ bib ]
[98] Antti Airola, Tapio Pahikkala, Willem Waegeman, Bernard De Baets, and Tapio Salakoski. A comparison of AUC estimators in small-sample studies. In Sašo Džeroski, Pierre Geurts, and Juho Rousu, editors, Proceedings of the third International Workshop on Machine Learning in Systems Biology, volume 8 of JMLR Workshop and Conference Proceedings, pages 3--13. Journal of Machine Learning Research, 2010. [ bib | .pdf ]
[99] Tapio Pahikkala, Willem Waegeman, Antti Airola, Tapio Salakoski, and Bernard De Baets. Conditional ranking on relational data. In José L. Balcázar, Francesco Bonchi, Aristides Gionis, and Michèle Sebag, editors, Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2010), volume 6322 of Lecture Notes in Computer Science, pages 499--514. Springer, 2010. [ bib | DOI | http ]
[100] Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Speeding up greedy forward selection for regularized least-squares. In Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, and Xingquan Zhu, editors, Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA'10), pages 325--330. IEEE Computer Society, December 2010. [ bib | DOI | .pdf ]
[101] Antti Airola, Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Applying permutation tests for assessing the statistical significance of wrapper based feature selection. In Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, and Xingquan Zhu, editors, Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA'10), pages 989--994. IEEE, December 2010. [ bib ]
[102] Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Large scale training methods for linear RankRLS. In Eyke Hüllermeier and Johannes Fürnkranz, editors, Proceedings of the ECML/PKDD-Workshop on Preference Learning (PL-10), 2010. [ bib ]
[103] Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Feature selection for regularized least-squares: New computational short-cuts and fast algorithmic implementations. In Samuel Kaski, David J. Miller, Erkki Oja, and Antti Honkela, editors, Proceedings of the Twentieth IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010), pages 295--300. IEEE, 2010. [ bib | DOI | http ]
[104] Tapio Pahikkala, Antti Airola, Pekka Naula, and Tapio Salakoski. Greedy RankRLS: a linear time algorithm for learning sparse ranking models. In Evgeniy Gabrilovich, Alexander J. Smola, and Naftali Tishby, editors, SIGIR 2010 Workshop on Feature Generation and Selection for Information Retrieval, pages 11--18. ACM, 2010. [ bib | .pdf ]
[105] Antti Airola, Tapio Pahikkala, Willem Waegeman, Bernard De Baets, and Tapio Salakoski. A comparison of AUC estimators in small-sample studies. In Sašo Džeroski, Pierre Geurts, and Juho Rousu, editors, Proceedings of the Third International Workshop on Machine Learning in Systems Biology (MLSB'09), pages 15--23, Helsinki, Finland, 2009. Helsinki University Printing House. [ bib ]
[106] Tapio Pahikkala, Willem Waegeman, Evgeni Tsivtsivadze, Tapio Salakoski, and Bernard De Baets. From ranking to intransitive preference learning: Rock-paper-scissors and beyond. In Eyke Hüllermeier and Johannes Fürnkranz, editors, Proceedings of the ECML/PKDD-Workshop on Preference Learning (PL-09), pages 84--100, 2009. [ bib ]
[107] Jari Björne, Juho Heimonen, Filip Ginter, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. Extracting complex biological events with rich graph-based feature sets. In Jun'ichi Tsujii, editor, Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task, pages 10--18. Association for Computational Linguistics, June 2009. [ bib | http ]
[108] Fabian Gieseke, Tapio Pahikkala, and Oliver Kramer. Fast evolutionary maximum margin clustering. In Léon Bottou and Michael Littman, editors, ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, volume 382 of ACM International Conference Proceeding Series, pages 361--368, New York, NY, USA, June 2009. ACM. [ bib | DOI | http | .pdf ]
[109] Tapio Pahikkala, Hanna Suominen, Jorma Boberg, and Tapio Salakoski. Efficient hold-out for subset of regressors. In Mikko Kolehmainen, Pekka Toivanen, and Bartlomiej Beliczynski, editors, Proceedings of the 9th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA'09), volume 5495 of Lecture Notes in Computer Science, pages 350--359, Berlin, Germany, 2009. Springer. [ bib | DOI | http ]
[110] Tapio Pahikkala, Willem Waegeman, Evgeni Tsivtsivadze, Bernard De Baets, and Tapio Salakoski. Learning intransitive reciprocal relations with regularized least-squares. In Menno van Zaanen, Herman Stehouwer, and Marieke van Erp, editors, Proceedings of the 18th Annual Belgian-Dutch Conference on Machine Learning (Benelearn 09), pages 13--20, Tilburg, The Netherlands, 2009. Tilburg centre for Creative Computing. [ bib ]
[111] Tapio Pahikkala, Antti Airola, Hanna Suominen, Jorma Boberg, and Tapio Salakoski. Efficient AUC maximization with regularized least-squares. In Anders Holst, Per Kreuger, and Peter Funk, editors, Tenth Scandinavian Conference on Artificial Intelligence, SCAI 2008, volume 173 of Frontiers in Artificial Intelligence and Applications, pages 12--19. IOS Press, Amsterdam, Netherlands, 2008. [ bib | .pdf ]
[112] Tapio Pahikkala, Antti Airola, Jorma Boberg, and Tapio Salakoski. Exact and efficient leave-pair-out cross-validation for ranking RLS. In Timo Honkela, Matti Pöllä, Mari-Sanna Paukkeri, and Olli Simula, editors, Proceedings of the 2nd International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR'08), pages 1--8, Espoo, Finland, 2008. Helsinki University of Technology. [ bib | .pdf ]
[113] Evgeni Tsivtsivadze, Fabian Gieseke, Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Learning preferences with co-regularized least squares. In Eyke Hüllermeier and Johannes Fürnkranz, editors, ECML/PKDD-Workshop on Preference Learning (PL-08), pages 55--62, 2008. [ bib ]
[114] Evgeni Tsivtsivadze, Tapio Pahikkala, Antti Airola, Jorma Boberg, and Tapio Salakoski. A sparse regularized least-squares preference learning algorithm. In Anders Holst, Per Kreuger, and Peter Funk, editors, Tenth Scandinavian Conference on Artificial Intelligence, SCAI 2008, volume 173 of Frontiers in Artificial Intelligence and Applications, pages 76--83. IOS Press, 2008. [ bib ]
[115] Hanna Suominen, Tapio Pahikkala, and Tapio Salakoski. Critical points in assessing learning performance via cross-validation. In Timo Honkela, Matti Pöllä, Mari-Sanna Paukkeri, and Olli Simula, editors, Proceedings of the 2nd International and Interdiciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR 2008), pages 9--22, Espoo, Finland, 2008. Helsinki University of Technology. [ bib ]
[116] Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, and Tapio Salakoski. A graph kernel for protein-protein interaction extraction. In Dina Demner-Fushman, Sophia Ananiadou, Kevin Bretonnel Cohen, John Pestian, Jun'ichi Tsujii, and Bonnie Webber, editors, Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing (BioNLP'08), pages 1--9, Stroudsburg, PA, USA, 2008. Association for Computational Linguistics. [ bib | .pdf ]
[117] Tapio Pahikkala, Hanna Suominen, Jorma Boberg, and Tapio Salakoski. Transductive ranking via pairwise regularized least-squares. In P Frasconi, K Kersting, and K Tsuda, editors, The 5th International Workshop on Mining and Learning with Graphs (MLG'07), pages 175--178, 2007. [ bib ]
[118] Tapio Pahikkala, Evgeni Tsivtsivadze, Antti Airola, Jorma Boberg, and Tapio Salakoski. Learning to rank with pairwise regularized least-squares. In Thorsten Joachims, Hang Li, Tie-Yan Liu, and ChengXiang Zhai, editors, SIGIR 2007 Workshop on Learning to Rank for Information Retrieval, pages 27--33, 2007. [ bib | .pdf ]
[119] Marketta Hiissa, Tapio Pahikkala, Hanna Suominen, Tuija Lehtikunnas, Barbro Back, Eija Helena Karsten, Sanna Salanterä, and Tapio Salakoski. Towards automated classification of intensive care nursing narratives. In A Hasman, R Haux, J Van Der Lei, E De Clercq, and FH Roger France, editors, Ubiquity: Technologies for Better Health in Aging Societies. Proceedings of MIE 2006, the 20th International Congress of the European Federation of Medical Informatics, volume 124 of Studies in Health Technology and Informatics, pages 789--794, Amsterdam, the Netherlands, 2006. IOS Press. [ bib ]
[120] Tapio Pahikkala, Jorma Boberg, Aleksandr Mylläri, and Tapio Salakoski. Incorporating external information in bayesian classifiers via linear feature transformations. In Tapio Salakoski, Filip Ginter, Sampo Pyysalo, and Tapio Pahikkala, editors, Proceedings of the 5th International Conference on Natural Language Processing FinTAL 06, Turku, Finland, volume 4139 of Lecture Notes in Artificial Intelligence, pages 399--410, Heidelberg, 2006. Springer. [ bib | .pdf ]
[121] Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Locality-convolution kernel and its application to dependency parse ranking. In Moonis Ali and Richard Dapoigny, editors, Proceedings of the The 19th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, volume 4031 of Lecture Notes in Artificial Intelligence, pages 610--618, Berlin, 2006. Springer. [ bib ]
[122] Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Fast n-fold cross-validation for regularized least-squares. In Timo Honkela, Tapani Raiko, Jukka Kortela, and Harri Valpola, editors, Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), volume 22 of Publications of the Finnish Artificial Intelligence Society, pages 83--90, Espoo, Finland, 2006. Helsinki University of Technology. [ bib | .pdf ]
[123] Tapio Pahikkala, Evgeni Tsivtsivadze, Jorma Boberg, and Tapio Salakoski. Graph kernels versus graph representations: a case study in parse ranking. In Thomas Gärtner, Gemma C. Garriga, and Thorsten Meinl, editors, Proceedings of the ECML/PKDD'06 workshop on Mining and Learning with Graphs (MLG'06), Berlin, Germany, 2006. [ bib | .pdf ]
[124] Hanna Suominen, Tapio Pahikkala, Marketta Hiissa, Tuija Lehtikunnas, Barbro Back, Helena Karsten, Sanna Salanterä, and Tapio Salakoski. Relevance ranking of intensive care nursing narratives. In Bogdan Gabrys, Robert J. Howlett, and Lakhmi C. Jain, editors, Knowledge-Based Intelligent Information and Engineering Systems. Proceedings of the 10th International Conference, KES 2006, Part I, volume 4251 of Lecture Notes in Computer Science, pages 720--727, Berlin / Heidelberg, Germany, 2006. Springer. [ bib | http ]
[125] Evgeni Tsivtsivadze, Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Aleksandr Mylläri, and Tapio Salakoski. Regularized least-squares for parse ranking. In A. Fazel Famili, Joost N. Kok, José Manuel Peña, Arno Siebes, and A. J. Feelders, editors, Proceedings of the 6th International Symposium on Intelligent Data Analysis, volume 3646 of Lecture Notes in Computer Science, pages 464--474, Berlin, September 2005. Springer. [ bib ]
[126] Tapio Pahikkala, Sampo Pyysalo, Filip Ginter, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Kernels incorporating word positional information in natural language disambiguation tasks. In Ingrid Russell and Zdravko Markov, editors, Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, pages 442--447, Menlo Park, CA, USA, May 2005. AAAI Press. [ bib | .pdf ]
[127] Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Aleksandr Mylläri, and Tapio Salakoski. Improving the performance of bayesian and support vector classifiers in word sense disambiguation using positional information. In Timo Honkela, Ville Könönen, Matti Pöllä, and Olli Simula, editors, Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, pages 90--97, Espoo, Finland, 2005. Helsinki University of Technology. [ bib | .pdf ]
[128] Filip Ginter, Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Extracting protein-protein interaction sentences by applying rough set data analysis. In Husaku Tsumoto, Roman Slowiński, Jan Komorowski, and Jerzy W. Grzymala-Busse, editors, Proceedings of the Fourth International Conference on Rough Sets and Current Trends in Computing, Uppsala, Sweden, volume 3066 of Lecture Notes in Computer Science, pages 780--785. Springer, Heidelberg, June 2004. [ bib ]
[129] Sampo Pyysalo, Filip Ginter, Tapio Pahikkala, Jeppe Koivula, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. Analysis of Link Grammar on biomedical dependency corpus targeted at protein-protein interactions. In Nigel Collier, Patrick Ruch, and Adeline Nazarenko, editors, Proceedings of Joint Workshop on Natural Language Processing in Biomedicine and its Applications JNLPBA 04, Geneva, Switzerland, pages 15--21, August 2004. [ bib ]

Book Chapters

[130] Tapio Pahikkala, Antti Airola, Thomas Canhao Xu, Pasi Liljeberg, Hannu Tenhunen, and Tapio Salakoski. On parallel online learning for adaptive embedded systems. In Seppo Virtanen, editor, Advancing Embedded Systems and Real-Time Communications with Emerging Technologies, chapter 11, pages 262--241. IGI Global, Hershey, PA, USA, 2014. [ bib ]
[131] Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski, and Tom Heskes. Co-regularized least-squares for label ranking. In Johannes Fürnkranz and Eyke Hüllermeier, editors, Preference Learning, chapter 6, pages 107--123. Springer, Berlin Heidelberg, 1st edition, 2010. [ bib | DOI | http ]
[132] Hanna Suominen, Sampo Pyysalo, Marketta Hiissa, Filip Ginter, Shuhua Liu, Dorina Marghescu, Tapio Pahikkala, Barbro Back, Helena Karsten, and Tapio Salakoski. Performance evaluation measures for text mining. In M Song and Y-FB Wu, editors, Handbook of Research on Text and Web Mining Technologies, pages 724--747. IGI Global, Hershey, Pennsylvania, USA, 2008. [ bib ]
[133] Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, and Tapio Salakoski. Kernel methods for text analysis. In Ying Liu, Aixin Sun, Han Tong Loh, Wen Feng Lu, and Ee-Peng Lim, editors, Advances of Computational Intelligence in Industrial Systems, volume 116 of Studies in Computational Intelligence, pages 81--97. Springer, 2008. [ bib ]

Articles in National or Non-Refereed Conference Proceedings, Extended Abstracts, and Other Publications

[134] Kaisa Linderborg, Anu Nuora, Tuomo Tupasela, Raija Tahvonen, Susanna Rokka, Matti Viitanen, Petri Mäkelä, Jonne Pohjankukka, Tapio Pahikkala, Baoru Yang, and Heikki Kallio. Effect of homogenisation of cow’s milk on postprandial lipemia, gastrointestinal symptoms and intestinal pressure in sensitive individuals. In 15th Euro Fed Lipid Congress, 2017. [ bib | http ]
[135] Harri Merisaari, Parisa Movahedi, Ileana Montoya Perez, Jussi Toivonen, Marko Pesola, Pekka Taimen, Peter Boström, Tapio Pahikkala, Hannu J. Aronen, and Ivan Jambor. Diffusion weighted imaging of prostate cancer: mathematical modeling of signal obtained using low b values. In 24th Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2016. [ bib ]
[136] Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, and Willem Waegeman. A two-step method to incorporate task features for large output spaces. In Manik Varma and Moustapha Cissé, editors, The NIPS Workshop on Multi-class and Multi-label Learning in Extremely Large Label Spaces (Extreme Classification 2015), December 2015. [ bib ]
[137] Paavo Nevalainen, Jonne Pohjankukka, Tapio Pahikkala, Raimo Sutinen, Jari Varjo, and Jukka Heikkonen. Open natural resource data in forecasting harvester mobility and infrastructure properties. In Federated Computer Science Event (YTP 2014), 2014. [ bib ]
[138] Anna Cichonska, Tapio Pahikkala, Antti Airola, Juho Rousu, and Tero Aittokallio. Predicting binding affinities between drug compounds and kinase targets. In Florence d'Alché Buc and Pierre Geurts, editors, The eighth International Workshop on Machine Learning in Systems Biology (MLSB 2014), page 82, September 2014. [ bib ]
[139] Michiel Stock, Bernard De Baets, Willem Waegeman, Thomas Fober, Eyke Hüllermeier, Tapio Pahikkala, and Antti Airola. Enzyme annotation using conditional ranking algorithms. In Benoît Fréenay, Michel Verleysen, and Pierre Dupont, editors, Proceedings of the 23rd Annual Belgian-Dutch Conference on Machine Learning (Benelearn'14), June 2014. [ bib ]
[140] Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, and Willem Waegeman. Pairwise kernel methods for predicting molecular interactions. In BeNeLux Bioinformatics Conference, page 15, December 2013. [ bib ]
[141] Willem Waegeman, Michiel Stock, Bernard De Baets, Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Conditional ranking algorithms for efficient object retrieval and object querying on relational data. In Thomas Demeester, Johannes Deleu, Laurent Mertens, Dieter Plaetinck, An De Moor, Thong Hoang, Tim Wauters, Chris Develder, Brecht Vermeulen, and Piet Demeester, editors, Proceedings of the 12th Dutch-Belgian Information Retrieval Workshop (DIR 2012), pages 59--60. Ghent University, 2012. [ bib ]
[142] Tapio Pahikkala, Evgeni Tsivtsivadze, Antti Airola, and Tapio Salakoski. Regularized least-squares for learning non-transitive preferences between strategies. In Tapani Raiko, Pentti Haikonen, and Jaakko Väyrynen, editors, Proceedings of the 13th Finnish Artificial Intelligence Conference and Nokia Workshop on Machine Consciousness, volume 24 of Publications of the Finnish Artificial Intelligence Society, pages 94--98. Finnish Artificial Intelligence Society, 2008. [ bib ]
[143] Hanna Suominen, Filip Ginter, Sampo Pyysalo, Antti Airola, Tapio Pahikkala, Sanna Salanterä, and Tapio Salakoski. Machine learning to automate the assignment of diagnosis codes to free-text radiology reports: a method description. In Milos Hauskrecht, Dale Schuurmans, and Csaba Szepesvari, editors, Proceedings of the ICML/UAI workshop on Machine Learning in health care applications, 2008. [ bib ]
[144] Filip Ginter, Tapio Pahikkala, Sampo Pyysalo, Evgeni Tsivtsivadze, Jorma Boberg, Jouni Järvinen, Aleksandr Mylläri, and Tapio Salakoski. Information extraction from biomedical text: The BioText project. In Margit Langemets and Penjam Priit, editors, Proceedings of the Second Baltic Conference on Human Language Technologies HLT 05, Tallinn, Estonia, pages 131--136. Institute of Cybernetics (Tallinn University of Technology), April 2005. [ bib ]

PhD Thesis

[145] Tapio Pahikkala. New Kernel Functions and Learning Methods for Text and Data Mining. PhD thesis, Turku Centre for Computer Science (TUCS), Turku, Finland, June 2008. [ bib ]

Technical Reports and Preprints

[146] Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, and Willem Waegeman. Efficient pairwise learning using kernel ridge regression: an exact two-step method. ArXiv e-prints, June 2016. [ bib ]
[147] Tapio Pahikkala, Markus Viljanen, Antti Airola, and Willem Waegeman. Spectral analysis of symmetric and anti-symmetric pairwise kernels, 2015. http://arxiv.org/abs/1506.05950. [ bib | arXiv ]
[148] Tapio Pahikkala, Antti Airola, and Tapio Salakoski. Linear time feature selection for regularized least-squares, 2010. http://arxiv.org/abs/1003.3570. [ bib | arXiv ]
[149] Tapio Pahikkala, Tuomas Nikula, Juha Mykkänen, Kirsti Näntö-Salonen, Olli Simell, Riitta Lahesmaa, Olli S. Nevalainen, and Tero Aittokallio. Considerations when using gene expression microarray data to diagnostic classification. Technical Report 719, TUCS, Turku Centre for Computer Science, Turku, Finland, 2005. [ bib ]