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[1]
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Ilkka Suuronen, Antti Airola, Tapio Pahikkala, Mika Murtojärvi, Valtteri
Kaasinen, and Henry Railo.
Budget-based classification of parkinson's disease from resting state
EEG.
IEEE Journal of Biomedical and Health Informatics,
27(8):3740--3747, 2023.
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DOI |
http ]
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[2]
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Riikka Numminen, Ileana Montoya Perez, Ivan Jambor, Tapio Pahikkala, and Antti
Airola.
Quicksort leave-pair-out cross-validation for ROC curve analysis.
Computational Statistics, 38(3):1579--1595, 2023.
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DOI |
http ]
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[3]
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Markus Viljanen, Antti Airola, and Tapio Pahikkala.
Generalized vec trick for fast learning of pairwise kernel models.
Machine Learning, 111(2):543--573, 2022.
[ bib |
DOI |
http ]
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[4]
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Riikka Numminen, Markus Viljanen, and Tapio Pahikkala.
Bayesian inference for predicting the monetization percentage in
free-to-play games.
IEEE Transactions on Games, 14(1):13--22, 2022.
[ bib |
DOI |
http ]
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[5]
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Tianduanyi Wang, Sandor Szedmak, Haishan Wang, Tero Aittokallio, Tapio
Pahikkala, Anna Cichonska, and Juho Rousu.
Modeling drug combination effects via latent tensor reconstruction.
Bioinformatics, 37(Supplement 1):i93--i101, 07 2021.
[ bib |
DOI |
http ]
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[6]
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Ileana Montoya Perez, Harri Merisaari, Ivan Jambor, Otto Ettala, Pekka Taimen,
Juha Knaapila, Henna Kekki, Ferdhos L. Khan, Elise Syrjälä, Aida
Steiner, Kari T. Syvänen, Janne Verho, Marjo Seppänen, Antti
Rannikko, Jarno Riikonen, Tuomas Mirtti, Tarja Lamminen, Jani Saunavaara, Ugo
Falagario, Alberto Martini, Tapio Pahikkala, Kim Pettersson, Peter J.
Boström, and Hannu J. Aronen.
Detection of prostate cancer using biparametric prostate mri,
radiomics, and kallikreins: A retrospective multicenter study of men with a
clinical suspicion of prostate cancer.
Journal of Magnetic Resonance Imaging, 55(2):465--477, 2021.
[ bib |
DOI ]
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[7]
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Aki Koivu, Mikko Sairanen, Antti Airola, Tapio Pahikkala, Wing-cheong Leung,
Tsz-kin Lo, and Daljit Singh Sahota.
Adaptive risk prediction system with incremental and transfer
learning.
Computers in Biology and Medicine, 138:104886, 2021.
[ bib |
DOI |
http ]
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[8]
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Salla Hakkola, Lotta Nylund, Natalia Rosa-Sibakov, Baoru Yang, Emilia Nordlund,
Tapio Pahikkala, Marko Kalliomäki, Anna-Marja Aura, and Kaisa M.
Linderborg.
Effect of oat b-glucan of different molecular weights on fecal bile
acids, urine metabolites and pressure in the digestive tract – a human
cross over trial.
Food Chemistry, 342:128219, 2021.
[ bib |
DOI ]
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[9]
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Juha Knaapila, Ivan Jambor, Otto Ettala, Pekka Taimen, Janne Verho, Ileana
Montoya Perez, Aida Kiviniemi, Tapio Pahikkala, Harri Merisaari, Tarja
Lamminen, Jani Saunavaara, Hannu J. Aronen, Kari T. Syvänen, and Peter J.
Boström.
Negative predictive value of biparametric prostate magnetic resonance
imaging in excluding significant prostate cancer: A pooled data analysis
based on clinical data from four prospective, registered studies.
European Urology Focus, 7(3):522--531, 2021.
[ bib |
DOI |
http ]
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[10]
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Farhoud Hosseinpour, Ahmad Naebi, Seppo Virtanen, Tapio Pahikkala, Hannu
Tenhunen, and Juha Plosila.
A resource management model for distributed multi-task applications
in fog computing networks.
IEEE Access, 9:152792--152802, 2021.
[ bib |
DOI ]
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[11]
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Heli Julkunen, Anna Cichonska, Prson Gautam, Sandor Szedmak, Jane Douat, Tapio
Pahikkala, Tero Aittokallio, and Juho Rousu.
Leveraging multi-way interactions for systematic prediction of
pre-clinical drug combination effects.
Nature Communications, 11(1), 2020.
[ bib |
DOI |
http ]
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[12]
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Mika Murtojärvi, Anni S. Halkola, Antti Airola, Teemu D. Laajala, Tuomas
Mirtti, Tero Aittokallio, and Tapio Pahikkala.
Cost-effective survival prediction for patients with advanced
prostate cancer using clinical trial and real-world hospital registry
datasets.
International Journal of Medical Informatics, 133:104014, 2020.
[ bib |
DOI |
http ]
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[13]
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Michiel Stock, Tapio Pahikkala, Antti Airola, Willem Waegeman, and Bernard
De Baets.
Algebraic shortcuts for leave-one-out cross-validation in supervised
network inference.
Briefings in Bioinformatics, 21(1):262--271, January 2020.
[ bib |
DOI |
http ]
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[14]
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Parisa Movahedi, Harri Merisaari, Ileana Montoya Perez, Pekka Taimen, Jukka
Kemppainen, Anna Kuisma, Olli Eskola, Jarmo Teuho, Jani Saunavaara, Marko
Pesola, Esa Kähkönen, Otto Ettala, Timo Liimatainen, Tapio Pahikkala,
Peter Boström, Hannu Aronen, Heikki Minn, and Ivan Jambor.
Prediction of prostate cancer aggressiveness using 18 F-Fluciclovine
(FACBC) PET and multisequence multiparametric MRI.
Scientific Reports, 10(1):1--11, 2020.
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[15]
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Ivan Jambor, Ugo Falagario, Parita Ratnani, Ileana Montoya Perez, Kadir Demir,
Harri Merisaari, Stanislaw Sobotka, George K. Haines, Alberto Martini,
Alp Tuna Beksac, Sara Lewis, Tapio Pahikkala, Peter Wiklund, Sujit Nair, and
Ash Tewari.
Prediction of biochemical recurrence in prostate cancer patients who
underwent prostatectomy using routine clinical prostate multiparametric mri
and decipher genomic score.
Journal of Magnetic Resonance Imaging, 51(4):1075--1085, 2020.
[ bib |
DOI |
http ]
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[16]
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Aki Koivu, Mikko Sairanen, Antti Airola, and Tapio Pahikkala.
Synthetic minority oversampling of vital statistics data with
generative adversarial networks.
Journal of the American Medical Informatics Association, 2020.
[ bib |
DOI |
http ]
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[17]
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Ileana Montoya Perez, Ivan Jambor, Tommi Kauko, Janne Verho, Otto Ettala, Ugo
Falagario, Harri Merisaari, Aida Kiviniemi, Pekka Taimen, Kari T.
Syvänen, Juha Knaapila, Marjo Seppänen, Antti Rannikko, Jarno
Riikonen, Markku Kallajoki, Tuomas Mirtti, Tarja Lamminen, Jani Saunavaara,
Tapio Pahikkala, Peter J. Boström, and Hannu J. Aronen.
Qualitative and quantitative reporting of a unique biparametric mri:
Towards biparametric mri-based nomograms for prediction of prostate biopsy
outcome in men with a clinical suspicion of prostate cancer (improd and
multi-improd trials).
Journal of Magnetic Resonance Imaging, 51(5):1556--1567, 2020.
[ bib |
DOI |
http ]
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[18]
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Markus Viljanen, Antti Airola, Anne-Maarit Majanoja, Jukka Heikkonen, and Tapio
Pahikkala.
Measuring player retention and monetization using the mean cumulative
function.
IEEE Transactions on Games, 12(1):101--114, 2020.
[ bib |
DOI |
arXiv ]
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[19]
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Petra Virjonen, Valtteri Hongisto, Marko M Mäkelä, and Tapio Pahikkala.
Optimized reference spectrum for rating the façade sound
insulation.
The Journal of the Acoustical Society of America,
148(5):3107--3116, 2020.
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[20]
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Ileana Montoya Perez, Ivan Jambor, Tapio Pahikkala, Antti Airola, Harri
Merisaari, Jani Saunavaara, Saeid Alinezhad, Riina-Minna
Väänänen, Terhi Tallgrén, Janne Verho, Aida Kiviniemi, Otto
Ettala, Juha Knaapila, Kari T. Syvänen, Markku Kallajoki, Paula Vainio,
Hannu J. Aronen, Kim Pettersson, Peter J. Boström, and Pekka Taimen.
Prostate cancer risk stratification in men with a clinical suspicion
of prostate cancer using a unique biparametric MRI and expression of 11
genes in apparently benign tissue: Evaluation using machine-learning
techniques.
Journal of Magnetic Resonance Imaging, 51(5):1540--1553, 2020.
[ bib |
DOI |
http ]
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[21]
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Aura Salmivaara, Samuli Launiainen, Jari Perttunen, Paavo Nevalainen, Jonne
Pohjankukka, Jari Ala-Ilomäki, Matti Sirén, Ari Laurén, Sakari
Tuominen, Jori Uusitalo, Tapio Pahikkala, Jukka Heikkonen, and Leena
Finér.
Towards dynamic forest trafficability prediction using open spatial
data, hydrological modelling and sensor technology.
Forestry: An International Journal of Forest Research, 2020.
[ bib |
DOI |
http ]
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[22]
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Riitta Mieronkoski, Elise Syrjälä, Mingzhe Jiang, Amir Rahmani, Tapio
Pahikkala, Pasi Liljeberg, and Sanna Salanterä.
Developing a pain intensity prediction model using facial expression:
A feasibility study with electromyography.
PLOS ONE, 15(7):1--15, 07 2020.
[ bib |
DOI |
http ]
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[23]
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Juha Knaapila, Ivan Jambor, Ileana Montoya Perez, Otto Ettala, Pekka Taimen,
Janne Verho, Aida Kiviniemi, Tapio Pahikkala, Harri Merisaari, Tarja
Lamminen, Jani Saunavaara, Hannu J. Aronen, Kari T. Syvänen, and Peter J.
Boström.
Prebiopsy IMPROD biparametric magnetic resonance imaging combined
with prostate-specific antigen density in the diagnosis of prostate cancer:
An external validation study.
European Urology Oncology, 3(5):648 -- 656, 2020.
[ bib |
DOI |
http ]
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[24]
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Golnaz Sahebi, Parisa Movahedi, Masoumeh Ebrahimi, Tapio Pahikkala, Juha
Plosila, and Hannu Tenhunen.
Gefes: A generalized wrapper feature selection approach for
optimizing classification performance.
Computers in Biology and Medicine, 125:103974, 2020.
[ bib ]
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[25]
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Ileana Montoya Perez, Antti Airola, Peter J Boström, Ivan Jambor, and Tapio
Pahikkala.
Tournament leave-pair-out cross-validation for receiver operating
characteristic analysis.
Statistical Methods in Medical Research, 28(10-11):2975--2991,
2019.
[ bib |
DOI |
http ]
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[26]
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Antti Airola, Jonne Pohjankukka, Johanna Torppa, Maarit Middleton, Vesa
Nykänen, Jukka Heikkonen, and Tapio Pahikkala.
Reliable AUC estimation of spatial classifiers, with application to
mineral prospectivity mapping.
Data Mining and Knowledge Discovery, 33(3):730--747, May 2019.
[ bib |
DOI |
http ]
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[27]
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Tanja Seppälä, Tuuli Ruponen, Mari Sandell, Parisa Movahedi,
Ileana Montoya Perez, Leo Lepistö, Oskar Laaksonen, Tapio Pahikkala,
Harri Härmä, and Sari Pihlasalo.
Luminometric label array for quantification of metal ions in drinking
water --- comparison to human taste panel.
Microchemical Journal, 145:204 -- 209, 2019.
[ bib |
DOI |
http ]
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[28]
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Iman Azimi, Tapio Pahikkala, Amir M. Rahmani, Hannakaisa Niela-Vilén, Anna
Axelin, and Pasi Liljeberg.
Missing data resilient decision-making for healthcare IoT through
personalization: A case study on maternal health.
Future Generation Computer Systems, 96:297--308, 2019.
[ bib |
DOI |
http ]
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[29]
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Harri Merisaari, Ivan Jambor, Otto Ettala, Peter J. Boström, Ileana
Montoya Perez, Janne Verho, Aida Kiviniemi, Kari Syvänen, Esa
Kähkönen, Lauri Eklund, Tapio Pahikkala, Paula Vainio, Jani
Saunavaara, Hannu J. Aronen, and Pekka Taimen.
IMPROD biparametric MRI in men with a clinical suspicion of prostate
cancer (IMPROD Trial): Sensitivity for prostate cancer detection in
correlation with whole-mount prostatectomy sections and implications for
focal therapy.
Journal of Magnetic Resonance Imaging, 2019.
In press. Available online.
[ bib |
DOI |
http ]
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[30]
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Henri Tenhunen, Tapio Pahikkala, Olli Nevalainen, Jukka Teuhola, Heta Mattila,
and Esa Tyystjärvi.
Automatic detection of cereal rows by means of pattern recognition
techniques.
Computers and Electronics in Agriculture, 162:677 -- 688, 2019.
[ bib |
DOI |
http ]
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[31]
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Jussi Toivonen, Ileana Montoya Perez, Parisa Movahedi, Harri Merisaari, Marko
Pesola, Pekka Taimen, Peter J. Boström, Jonne Pohjankukka, Aida
Kiviniemi, Tapio Pahikkala, Hannu J. Aronen, and Ivan Jambor.
Radiomics and machine learning of multisequence multiparametric
prostate MRI: Towards improved non-invasive prostate cancer
characterization.
PLOS ONE, 14(7):1--23, 07 2019.
[ bib |
DOI |
http ]
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[32]
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Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, and Willem
Waegeman.
A comparative study of pairwise learning methods based on kernel
ridge regression.
Neural Computation, 30(8):2245--2283, 2018.
[ bib |
DOI |
arXiv |
http ]
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[33]
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Anna Cichonska, Tapio Pahikkala, Sandor Szedmak, Heli Julkunen, Antti Airola,
Markus Heinonen, Tero Aittokallio, and Juho Rousu.
Learning with multiple pairwise kernels for drug bioactivity
prediction.
Bioinformatics, 34(13):i509--i518, 2018.
[ bib |
DOI |
http ]
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[34]
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Antti Airola and Tapio Pahikkala.
Fast kronecker product kernel methods via generalized vec trick.
IEEE Transactions on Neural Networks and Learning Systems,
29(8):3374--3387, 2018.
[ bib |
DOI |
arXiv |
http ]
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[35]
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Tiina Lipiäinen, Jenni Pessi, Parisa Movahedi, Juha Tapio Koivistoinen,
Lauri Kurki, Mari Tenhunen, Jouko Yliruusi, Anne M. Juppo, Jukka Heikkonen,
Tapio Pahikkala, and Clare J. Strachan.
Time-gated raman spectroscopy for quantitative determination of
solid-state forms of fluorescent pharmaceuticals.
Analytical Chemistry, 90(7):4832--4839, 2018.
[ bib |
DOI |
http ]
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[36]
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Virpi Talman, Jaakko Teppo, Päivi Pöhö, Parisa Movahedi, Anu
Vaikkinen, Tuuli Karhu, Kajetan Trost, Tommi Suvitaival, Jukka Heikkonen,
Tapio Pahikkala, Tapio Kotiaho, Risto Kostiainen, Markku Varjosalo, and
Heikki Ruskoaho.
Molecular atlas of postnatal mouse heart development.
Journal of the American Heart Association, 7(20):e010378, 2018.
[ bib |
DOI |
Preprint ]
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[37]
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Aki Koivu, Teemu Korpimäki, Petri Kivelä, Tapio Pahikkala, and Mikko
Sairanen.
Evaluation of machine learning algorithms for improved risk
assessment for down's syndrome.
Computers in Biology and Medicine, 98:1--7, July 2018.
[ bib |
DOI |
http ]
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[38]
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Anu Nuora, Tuomo Tupasela, Raija Tahvonen, Susanna Rokka, Pertti Marnila, Matti
Viitanen, Petri Mäkelä, Jonne Pohjankukka, Tapio Pahikkala, Baoru
Yang, Heikki Kallio, and Kaisa Linderborg.
Effect of homogenised and pasteurised versus native cows' milk on
gastrointestinal symptoms, intestinal pressure and postprandial lipid
metabolism.
International Dairy Journal, 79:15--23, 2018.
[ bib |
DOI |
http ]
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[39]
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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, 43(1):90--98, 2018.
[ bib |
DOI |
http ]
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[40]
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Jonne Pohjankukka, Sakari Tuominen, Juho Pitkänen, Tapio Pahikkala, and
Jukka Heikkonen.
Comparison of estimators and feature selection procedures in forest
inventory based on airborne laser scanning and digital aerial imagery.
Scandinavian Journal of Forest Research, 33(7):681--694, 2018.
[ bib |
DOI |
http ]
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[41]
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Markus Viljanen, Antti Airola, Jukka Heikkonen, and Tapio Pahikkala.
Playtime measurement with survival analysis.
IEEE Transactions on Games, 10(2):128--138, June 2018.
[ bib |
DOI |
arXiv |
http ]
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[42]
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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, 5(5):485--497.e3, November 2017.
[ bib |
DOI |
http ]
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[43]
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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 ]
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[44]
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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 ]
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[45]
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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 |
.pdf ]
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[46]
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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 ]
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[47]
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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 ]
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[48]
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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 ]
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[49]
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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 ]
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[50]
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Jukka Aukia, Juho Heimonen, Tapio Pahikkala, and Tapio Salakoski.
Automated quantification of reuters news using a receiver operating
characteristic curve analysis: The western media image of china.
Global Media and China, 2(3-4):251--268, 2017.
[ bib |
DOI |
http ]
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[51]
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Paavo Nevalainen, Aura Salmivaara, Jari Ala-Ilomäki, Samuli Launiainen,
Juuso Hiedanpää, Leena Finér, Tapio Pahikkala, and Jukka
Heikkonen.
Estimating the rut depth by UAV photogrammetry.
Remote Sensing, 9(12), 2017.
[ bib |
DOI |
http ]
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[52]
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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 ]
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[53]
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Tapio Pahikkala and Antti Airola.
Rlscore: Regularized least-squares learners.
Journal of Machine Learning Research, 17(221):1--5, 2016.
[ bib |
.html ]
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[54]
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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 ]
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[55]
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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 ]
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[56]
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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 ]
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[57]
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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 ]
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[58]
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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 ]
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[59]
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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 ]
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[60]
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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 ]
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[61]
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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 ]
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[62]
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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 ]
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[63]
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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 ]
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[64]
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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 ]
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[65]
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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 ]
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[66]
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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 ]
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[67]
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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 ]
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[68]
|
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 ]
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[69]
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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 ]
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[70]
|
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 |
.pdf ]
|
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[71]
|
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 |
.pdf ]
|
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[72]
|
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 ]
|
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[73]
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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 ]
|
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[74]
|
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 ]
|
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[75]
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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 ]
|
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[76]
|
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 ]
|
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[77]
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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 ]
|
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[78]
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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 ]
|
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[79]
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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 ]
|
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[80]
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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 ]
|
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[81]
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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 ]
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[82]
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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 ]
|
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[83]
|
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 ]
|
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[84]
|
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 ]
|
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[85]
|
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 |
.pdf ]
|
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[86]
|
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 ]
|
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[87]
|
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 ]
|
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[88]
|
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 ]
|
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[89]
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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 ]
|
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[90]
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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 ]
|
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[91]
|
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 ]
|
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[92]
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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 ]
|
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[93]
|
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 ]
|
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[94]
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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 ]
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[95]
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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 ]
|
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[99]
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Parisa Movahedi, Valtteri Nieminen, Ileana Montoya Perez, Tapio Pahikkala, and
Antti Airola.
Evaluating classifiers trained on differentially private synthetic
health data.
In João Rafael Almeida, Myra Spiliopoulou, José Alberto
Benítez-Andrades, Giuseppe Placidi, Alejandro Rodríguez
González, Rosa Sicilia, and Bridget Kane, editors, 36th IEEE
International Symposium on Computer-Based Medical Systems (CBMS), pages
748--753. IEEE, 2023.
[ bib |
DOI ]
|
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[100]
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Markus Viljanen and Tapio Pahikkala.
Predicting unemployment with machine learning based on registry data.
In Fabiano Dalpiaz, Jelena Zdravkovic, and Pericles Loucopoulos,
editors, Research Challenges in Information Science, pages 352--368.
Springer International Publishing, 2020.
[ bib ]
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[101]
|
Markus Viljanen, Ajay Byanjankar, and Tapio Pahikkala.
Predicting profitability of peer-to-peer loans with recovery models
for censored data.
In Ireneusz Czarnowski, Robert J. Howlett, and Lakhmi C. Jain,
editors, Intelligent Decision Technologies, pages 15--25, Singapore,
2020. Springer Singapore.
[ bib ]
|
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[102]
|
Riikka Numminen, Markus Viljanen, and Tapio Pahikkala.
Predicting the monetization percentage with survival analysis in
free-to-play games.
In 2019 IEEE Conference on Games (CoG), pages 1--8, 2019.
[ bib ]
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[103]
|
Elise Syrjälä, Mingzhe Jiang, Tapio Pahikkala, Sanna Salanterä, and
Pasi Liljeberg.
Skin conductance response to gradual-increasing experimental pain.
In 2019 41st Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBC), pages 3482--3485. IEEE,
2019.
[ bib ]
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[104]
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Petra Virjonen, Paavo Nevalainen, Tapio Pahikkala, and Jukka Heikkonen.
Ship movement prediction using k-nn method.
In 2018 Baltic Geodetic Congress (BGC Geomatics), pages
304--309. IEEE, June 2018.
[ bib |
DOI ]
|
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[105]
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Markus Viljanen, Antti Airola, Jukka Heikkonen, and Tapio Pahikkala.
A/b-test of retention and monetization using the cox model.
In Brian Magerko and Jonathan P. Rowe, editors, Proceedings of
the Thirteenth AAAI Conference on Artificial Intelligence and Interactive
Digital Entertainment (AIIDE-17), pages 248--254. AAAI Press, October
2017.
[ bib |
DOI |
http |
.pdf ]
|
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[106]
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Paavo Nevalainen, Ivan Jambor, Jonne Pohjankukka, Jukka Heikkonen, and Tapio
Pahikkala.
Triangular curvature approximation of surfaces - filtering the
spurious mode.
In Maria De Marsico, Gabriella Sanniti di Baja, and Ana L. N. Fred,
editors, Proceedings of the 6th International Conference on Pattern
Recognition Applications and Methods, ICPRAM 2017, Porto, Portugal,
February 24-26, 2017, pages 684--692. SciTePress, 2017.
[ bib |
DOI |
http ]
|
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[107]
|
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 ]
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[108]
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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 ]
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[109]
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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 ]
|
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[110]
|
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 ]
|
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[111]
|
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 ]
|
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[112]
|
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.
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[113]
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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 ]
|
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[114]
|
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 ]
|
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[115]
|
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 ]
|
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[116]
|
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 ]
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[117]
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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 |
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|
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[118]
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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 |
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|
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[119]
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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 |
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Preprint ]
|
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[120]
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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.
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DOI ]
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[121]
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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.
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[122]
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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.
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DOI ]
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[123]
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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.
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[124]
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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.
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[125]
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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 ]
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[126]
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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.
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[127]
|
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 ]
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[128]
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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.
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|
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[129]
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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).
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[130]
|
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.
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[131]
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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.
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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.
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[133]
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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.
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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.
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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.
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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.
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[137]
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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.
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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.
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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.
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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.
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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.
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[142]
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Antti Airola, Tapio Pahikkala, Willem Waegeman, Bernard De Baets, and Tapio
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Evgeni Tsivtsivadze, Tapio Pahikkala, Antti Airola, Jorma Boberg, and Tapio
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A sparse regularized least-squares preference learning algorithm.
In Anders Holst, Per Kreuger, and Peter Funk, editors, Tenth
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Frontiers in Artificial Intelligence and Applications, pages 76--83.
IOS Press, 2008.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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