Paweł Teisseyre, PhD


  1. M. J. Dabrowski, M. Draminski, K. Diamanti, K. Stepniak, M. A. Mozolewska, P. Teisseyre, J. Koronacki, J. Komorowski, B. Kaminska and B. Wojtas, Unveiling new interdependencies between significant DNA methylation sites, gene expression profiles and glioma patients survival, Nature- Scientific Reports, 2018.
  2. J. Mielniczuk, P. Teisseyre, Deeper Look at Two Concepts of Measuring Gene-Gene Interactions: Logistic Regression and Interaction Information Revisited, Genetic Epidemiology, Volume 42 (2) 187-200, 2018.
  3. P. Teisseyre, CCnet: joint multi-label classification and feature selection using classifier chains and elastic net regularization, Neurocomputing, Volume 235, 98-111, 2017.
  4. M. Sydow, K. Baraniak, P. Teisseyre, Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia, Journal of Intelligent Information Systems (on-line), 2016.
  5. P. Teisseyre, Feature ranking for multi-label classification using Markov Networks, Neurocomputing, Volume 205, 439-454, 2016.
  6. P. Teisseyre, R. A. Klopotek, J. Mielniczuk, Random Subspace Method for High-Dimensional Regression with the R Package regRSM, Computational Statistics, Volume 31(3), 943-972, 2016 .
  7. J. Mielniczuk, P. Teisseyre, What do we choose when we err? Model selection and testing for misspecied logistic regression revisited, Challenges in Computational Statistics and Data Mining, Volume: 605 of the series Studies in Computational Intelligence, 271--296, 2015.
  8. P. Przybyła, P. Teisseyre, What do your look-alikes say about you? Exploiting strong and weak similarities for author profiling, Notebook for PAN at CLEF 2015.
  9. P. Przybyła, P. Teisseyre, Analysing Utterances in Polish Parliament to Predict Speaker's Background, Journal of Quantitative Linguistics, Volume 21 (4), 2014.
  10. J. Mielniczuk, P. Teisseyre, Using Random Subspace Method for Prediction and Variable Importance Assesment in Regression, Computational Statistics and Data Analysis, Volume 71, 725-742, 2014.
  11. P. Teisseyre, On some methods of model selection for linear and logistic regression, PhD dissertation, Warsaw, 2013.
  12. J. Mielniczuk, P. Teisseyre, Selection of regression and autoregression models with initial ordering of variables, Communications in Statistics, Theory and Methods, Volume 41 (24), 4484 - 4502, 2012.
  13. J. Mielniczuk, P. Teisseyre, Selection and prediction for linear models using Random Subspace Methods, Proceedings of the Conference Information Technologies: Research and their Interdisciplinary Applications, 2012.
  14. J. Mielniczuk, P. Teisseyre, Model selection in logistic regression using p-values and greedy search, Security and Intelligent Information Systems. LNCS 7053, Springer-Verlag Berlin Heidelberg, 128-141, 2011.
  15. L. Stapp, M. Pilarski, P. Stapp, P. Zgadzaj, P. Teisseyre, Dynamic Time Warping as a method for observing load possibility for CDN clusters, Proceedings of The Second International Multi-Conference on Complexity, Informatics, Cybernetics, Orlando, Florida, USA, 2011.