Jarkko Tikka

发表

Mixture Modeling of DNA Copy Number Amplification Patterns in Cancer

Jaakko Hollmén, Jarkko Tikka, Samuel Myllykangas, 2007, IWANN.

Common Subset Selection of Inputs in Multiresponse Regression

Timo Similä, Jarkko Tikka, J. Tikka, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Functional prediction of unidentified lipids using supervised classifiers

Jaakko Hollmén, Laxman Yetukuri, Jarkko Tikka, 2010, Metabolomics.

Selection of important input variables for RBF network using partial derivatives

Jaakko Hollmén, Jarkko Tikka, 2008, ESANN.

Combined input variable selection and model complexity control for nonlinear regression

Timo Similä, Jarkko Tikka, J. Tikka, 2009, Pattern Recognit. Lett..

Parameter Based Fatigue Life Analysis, Influence of Training Data Selection to Analysis Performance

Jussi Ahola, Jarkko Tikka, Mikko Hiirsalmi, 2006 .

Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions

Jaakko Hollmén, Jarkko Tikka, J. Hollmén, 2007, IDA.

Multiresponse Sparse Regression with Application to Multidimensional Scaling

Timo Similä, Jarkko Tikka, J. Tikka, 2005, ICANN.

INPUT VARIABLE SELECTION METHODS FOR CONSTRUCTION OF INTERPRETABLE REGRESSION MODELS

Jarkko Tikka, J. Tikka, 2008 .

Simultaneous input variable and basis function selection for RBF networks

Jarkko Tikka, J. Tikka, 2009, Neurocomputing.

Input Selection for Radial Basis Function Networks by Constrained Optimization

Jarkko Tikka, 2007, ICANN.

STRAIN GAUGE CAPABIILITIES IN CRACK DETECTION

Jarkko Tikka, Risto Hedman, Aslak Siljander, 2003 .

Input selection and shrinkage in multiresponse linear regression

Timo Similä, Jarkko Tikka, J. Tikka, 2007, Comput. Stat. Data Anal..

Input Selection for Long-Term Prediction of Time Series

Amaury Lendasse, Jaakko Hollmén, Jarkko Tikka, 2005, IWANN.

of Training Data Selection to Analysis Performance

Jussi Ahola, Jarkko Tikka, Mikko Hiirsalmi, 2006 .

FATIGUE LIFE EVALUATION OF CRITICAL LOCATIONS IN AIRCRAFT STRUCTURES USING VIRTUAL FATIGUE TEST

Jarkko Tikka, 2002 .

Sequential input selection algorithm for long-term prediction of time series

Jaakko Hollmén, Jarkko Tikka, J. Hollmén, 2008, Neurocomputing.

Long-term prediction of time series using a parsimonious set of inputs and LS-SVM

Jaakko Hollmén, Jarkko Tikka, 2007 .

Learning Linear Dependency Trees from Multivariate Time-series Data

Jaakko Hollmén, Jarkko Tikka, J. Hollmén, 2004 .

Analysis of Fast Input Selection: Application in Time Series Prediction

Amaury Lendasse, Jaakko Hollmén, Jarkko Tikka, 2006, ICANN.

Sparse Regression for Analyzing the Development of Foliar Nutrient Concentrations in Coniferous Trees

Mika Sulkava, Jaakko Hollmén, Jarkko Tikka, 2006 .