Jarkko Tikka

Contact Information

Research

Publications

Journal Articles

1. Jarkko Tikka.
   Simultaneous input variable and basis function selection for RBF networks.
   Neurocomputing, Elsevier, Accepted for publication.

2. Timo Simil~ and Jarkko Tikka.
   Combined input variable selection and model complexity control for nonlinear regression.
   Pattern Recognition Letters, Elsevier, Accepted for publication.

3. Jarkko Tikka and Jaakko Hollmén.
   Sequential input selection algorithm for long-term prediction of time series.
   Neurocomputing, Elsevier, Vol. 71(13-15), pages 2604-2615, August 2008.

4. Samuel Myllykangas, Jarkko Tikka, Tom B~hling, Sakari Knuutila, and Jaakko Hollmén.
   Classification of human cancers based on DNA copy number amplification modeling.
   BMC Medical Genomics, Vol. 1:15, May 2008.

5. Harri Keski-S~ntti, Timo Atula, Jarkko Tikka, Jaakko Hollmén, Antti A. M~kitie, and Ilmo Leivo.
   The predictive value of histopathologic parameters in early squamous cell carcinoma of oral tongue.
   Oral Oncology, Elsevier, Vol. 43(10), pages 1007-1013, November 2007.

6. Timo Simil~ and Jarkko Tikka.
   Input selection and shrinkage in multiresponse linear regression.
   Computatinal Statistics & Data Analysis, Elsevier, Vol. 52(1), pages 406-422, September 2007.

7. Mika Sulkava, Jarkko Tikka, and Jaakko Hollmén.
   Sparse regression for analyzing the development of foliar nutrient concentrations in coniferous trees.
   Ecological Modelling, Elsevier, vol. 191(1), pages 118-130, January 2006.

Conference Articles

1. Jarkko Tikka and Jaakko Hollmén.
   Selection of important input variables for RBF network using partial derivatives.
   In Michel Verleysen, editor, Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN 2008), d-side, pages 167-172, Brugge, Belgium, April 2008.

2. Jarkko Tikka.
   Input selection for radial basis function networks by constrained optimization.
   In Joaquim Marques de S~, Lu~s A. Alexandre, Wlodzislaw Duch, and Danilo Mandic, editors, Proceedings of the 17th International Conference on Artificial Neural Networks (ICANN 2007), LNCS 4668, © Springer-Verlag, pages 239-248, Porto, Portugal, September 2007.

3. Jaakko Hollmén and Jarkko Tikka.
   Compact and understandable descriptions of mixtures of Bernoulli distributions.
   In Michael R. Berthold, John Shawe-Taylor, and Nada Lavrač, editors, Proceedings of the 7th International Symposium on Intelligent Data Analysis (IDA 2007), LNCS 4723,
   © Springer-Verlag, pages 1-12, Ljubljana, Slovenia, September 2007.

4. Jarkko Tikka, Jaakko Hollmén, and Samuel Myllykangas.
   Mixture modeling of DNA copy number amplification patterns in cancer.
   In Francisco Sandoval, Alberto Prieto, Joan Cabestany, and Manuel Graña, editors, Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN 2007), LNCS 4507, © Springer-Verlag, pages 972-979, S~n Sebastian, Spain, June 2007.

5. Jarkko Tikka and Jaakko Hollmén.
   Long-term prediction of time series using a parsimonious set of inputs and LS-SVM.
   In Amaury Lendasse, editor, Proceedings of the First European Symposium on Time Series Prediction (ESTSP 2007), pages 87-96, Espoo, Finland, February 2007.

6. Jarkko Tikka, Amaury Lendasse, and Jaakko Hollmén.
   Analysis of fast input selection: Application in time series prediction.
   In Stefanos Kollias, Andreas Stafylopatis, Wlodzislaw Duch, and Erkki Oja, editors, Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN 2006), LNCS 4132, © Springer-Verlag, pages 161-170, Athens, Greece, September 2006.

7. Timo Simil~ and Jarkko Tikka.
   Common subset selection of inputs in multiresponse regression.
   In Proceedings of International Joint Conference on Neural Networks (IJCNN 2006),
   © IEEE, pages 1908-1915, Vancouver, Canada, July 2006.

8. Timo Simil~ and Jarkko Tikka.
   Multiresponse sparse regression with application to multidimensional scaling.
   In Wlodzislaw Duch, Janusz Kacprzyk, Erkki Oja, and Slawomir Zadrozny, editors, Proceedings of the 15th International Conference on Artificial Neural Networks (ICANN 2005), LNCS 3967, part II, © Springer-Verlag, pages 97-102, Warsaw, Poland, September 2005.
   (Matlab function of the Multiresponse Sparse Regression (MRSR) algorithm: mrsr.m)

9. Jarkko Tikka, Jaakko Hollmén, and Amaury Lendasse.
   Input selection for long-term prediction of time series.
   In Joan Cabestany, Alberto Prieto, and Francisco Sandoval, editors, Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN 2005), LNCS 3512, © Springer-Verlag, pages 1002-1009, Vilanova i la Geltr~, Barcelona, Spain, June 2005.

10. Jarkko Tikka and Jaakko Hollmén.
    Learning linear dependency trees from multivariate time-series data.
    In Proceedings of The Temporal Data Mining Workshop, in conjunction with The Fourth IEEE International Conference on Data Mining (ICDM 2004), Brighton, UK, November, 2004.

11. Mika Sulkava, Jarkko Tikka, and Jaakko Hollmén.
    Sparse regression for analyzing the development of foliar nutrient concentrations in coniferous trees.
    In Sašo Džeroski, Bernard Ženko, and Marko Debeljak, editors, Proceedings of the Fourth International Workshop on Environmental Applications of Machine Learning (EAML 2004), pages 57-58, Bled, Slovenia, September 2004.

Master's thesis