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[1]
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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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[2]
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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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[3]
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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, 2012.
Accepted for publication.
[ bib |
.pdf ]
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[4]
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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, pages 1-17, 2012.
Accepted for publication.
[ bib |
DOI |
http ]
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[5]
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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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[6]
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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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[7]
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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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[8]
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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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[9]
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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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[10]
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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 ]
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[11]
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Rangaswamy Karthikeyan, Tapio Pahikkala, Seppo Virtanen, Jouni Isoaho,
K. Manickavasagam, and K. V. V. Murthy.
Fuzzy logic based control for parallel cascade control.
International Journal on Automatic Control and System
Engineering, 10(2):39-48, 2010.
[ bib ]
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[12]
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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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[13]
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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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[14]
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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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[15]
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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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[16]
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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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[17]
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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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[18]
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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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[19]
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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.
Recent Advances in Natural Language Processing for Biomedical
Applications, special issue of the International Journal of Medical
Informatics, 75(6):430-442, 2006.
[ bib ]
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[20]
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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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[21]
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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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[27]
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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.
[ bib ]
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[28]
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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 The 14th IEEE International Conference on High Performance
Computing and Communications (HPCC-2012). IEEE, 2012.
To appear.
[ bib ]
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[29]
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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.
[ bib |
DOI |
http ]
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[30]
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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 ]
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[31]
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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.
[ bib |
DOI ]
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[32]
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Sebastian Okser, Tapio Pahikkala, Antti Airola, 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 ]
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[33]
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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.
[ bib |
DOI |
http ]
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[34]
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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.
[ bib ]
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[35]
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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.
[ bib ]
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[36]
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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.
[ bib ]
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[37]
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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.
[ bib ]
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[38]
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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.
[ bib |
.pdf ]
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[39]
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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.
[ bib |
DOI |
http ]
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[40]
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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, December 2010.
[ bib |
DOI |
.pdf ]
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[41]
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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.
[ bib ]
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[42]
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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.
[ bib ]
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[43]
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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.
[ bib |
DOI |
http ]
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[44]
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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.
[ bib |
.pdf ]
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[45]
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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 (MLSB'09), pages 15-23, Helsinki, Finland, 2009. Helsinki
University Printing House.
[ bib ]
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[46]
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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.
[ bib ]
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[47]
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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.
[ bib |
http ]
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[48]
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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.
[ bib |
DOI |
http |
.pdf ]
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[49]
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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.
[ bib |
DOI |
http ]
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[50]
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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.
[ bib ]
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[51]
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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 ]
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[52]
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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.
[ bib |
.pdf ]
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[53]
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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.
[ bib ]
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[54]
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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 ]
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[55]
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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.
[ bib ]
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[56]
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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.
[ bib |
.pdf ]
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[57]
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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 ]
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[58]
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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.
[ bib ]
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[59]
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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.
[ bib |
.pdf ]
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[60]
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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, De Clercq E, 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 ]
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[61]
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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.
[ bib |
.pdf ]
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[62]
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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.
[ bib ]
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[63]
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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 ]
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[64]
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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.
[ bib ]
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[65]
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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.
[ bib |
http ]
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[66]
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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.
[ bib ]
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[67]
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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.
[ bib ]
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[68]
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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, 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.
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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 Slowinski, 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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[71]
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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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