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Statistics, econometrics and classification

  1. S. Sriboonchitta, J. Liu, A. Wiboonpongse and T. Denoeux. A double-copula stochastic frontier model with dependent error components and correction for sample selection. International Journal of Approximate Reasoning, Volume 80, January 2017, Pages 174-184. pdf
  2. S. Kanj, F. Abdallah, T. Denoeux and K. Tout. Editing training data for multi-label classification with the k-nearest neighbors rule. Pattern Analysis and Applications, Vol. 19, Issue 1, pp 145-161, 2016. pdf
  3. A. Wiboonpongse, J. Liu, S. Sriboonchitta and T. Denoeux. Modeling dependence between error components of the stochastic frontier model using copula: Application to Intercrop Coffee Production in Northern Thailand. International Journal of Approximate Reasoning, Vol. 65, Pages 34-44, 2015. pdf
  4. E. Côme, L. Oukhellou, T. Denoeux and P. Aknin. Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints. Pattern Analysis and Applications, Vol. 15, Number 3, pages 313-326, 2012. pdf
  5. Z. Younes, F. Abdallah, T. Denoeux and H. Snoussi. A dependent multi-label classification method derived from the k-nearest neighbor rule. EURASIP Journal on Advances in Signal Processing, vol. 2011, Article ID 645964, 14 pages, 2011. doi:10.1155/2011/645964. pdf
  6. T. Denoeux and G. Govaert. Un algorithme de classification automatique non paramétrique. Comptes-Rendus de l'Académie des Sciences , t. 324, Série I, p. 673-678, 1997. pdf

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