Neurocomputing

Research outputs

  1. 2018
  2. Published

    Supervised low rank indefinite kernel approximation using minimum enclosing balls

    Schleif, F. M., Gisbrecht, A. & Tino, P., 27 Nov 2018, In : Neurocomputing. 318, p. 213-226 14 p.

    Research output: Contribution to journalArticle

  3. Published

    Gaussian process classification for prediction of in-hospital mortality among preterm infants

    Rinta-Koski, O. P., Särkkä, S., Hollmén, J., Leskinen, M. & Andersson, S., 2018, In : Neurocomputing. 298, p. 134-141

    Research output: Contribution to journalArticle

  4. Published

    Stochastic Discriminant Analysis for Linear Supervised Dimension Reduction

    Juuti, M., Corona, F. & Karhunen, J., 2018, In : Neurocomputing. 291, p. 136-150 15 p.

    Research output: Contribution to journalArticle

  5. 2017
  6. Published

    What you see is what you can change: Human-centered machine learning by interactive visualization

    Sacha, D., Sedlmair, M., Zhang, L., Lee, J. A., Peltonen, J., Weiskopf, D., North, S. C. & Keim, D. A., 13 Dec 2017, In : Neurocomputing. 268, p. 164-175 12 p.

    Research output: Contribution to journalArticle

  7. Published

    Cluster ensemble selection with constraints

    Yang, F., Li, T., Zhou, Q. & Xiao, H., 26 Apr 2017, In : Neurocomputing. 235, p. 59-70 12 p.

    Research output: Contribution to journalArticle

  8. Published

    Adding reliability to ELM forecasts by confidence intervals

    Akusok, A., Gritsenko, A., Miche, Y., Björk, K. M., Nian, R., Lauren, P. & Lendasse, A., 5 Jan 2017, In : Neurocomputing. 219, p. 232-241 10 p.

    Research output: Contribution to journalArticle

  9. Published
  10. Published
  11. 2016
  12. Published

    ELMVIS+: Fast nonlinear visualization technique based on cosine distance and extreme learning machines

    Akusok, A., Baek, S., Miche, Y., Björk, K. M., Nian, R., Lauren, P. & Lendasse, A., 12 Sep 2016, In : Neurocomputing. 205, p. 247-263 17 p.

    Research output: Contribution to journalArticle

  13. Published

    Brain MRI morphological patterns extraction tool based on Extreme Learning Machine and majority vote classification

    Termenon, M., Grana, M., Savio, A., Akusok, A., Miche, Y., Bjork, K-M. & Lendasse, A., 22 Jan 2016, In : Neurocomputing. 174, p. 344-351 8 p.

    Research output: Contribution to journalArticle

  14. Published

    Singular Value Decomposition update and its application to (Inc)-OP-ELM

    Grigorevskiy, A., Miche, Y., Käpylä, M. & Lendasse, A., 22 Jan 2016, In : Neurocomputing. 174, p. 99-108 10 p.

    Research output: Contribution to journalArticle

  15. Published

    Self-organizing multiobjective optimization based on decomposition with neighborhood ensemble

    Zhang, H., Zhang, X., Gao, X-Z. & Song, S., 15 Jan 2016, In : Neurocomputing. 173, p. 1868-1884 17 p.

    Research output: Contribution to journalArticle

  16. 2015
  17. Published

    Self-organization and missing values in SOM and GTM

    Vatanen, T., Osmala, M., Raiko, T., Lagus, K., Sysi-Aho, M., Orešič, M., Honkela, T. & Lähdesmäki, H., 5 Jan 2015, In : Neurocomputing. 147, 1, p. 60-70 11 p.

    Research output: Contribution to journalArticle

  18. Published

    Binary/Ternary Extreme Learning Machines

    van Heeswijk, M. & Miche, Y., 2015, In : Neurocomputing. 149, Part A, p. 187-197

    Research output: Contribution to journalArticle

  19. Published

    Formation control of impulsive networked autonomous underwater vehicles under fixed and switching topologies

    Hu, Z., Ma, C., Zhang, L., Halme, A., Hayat, T. & Ahmad, B., 2015, In : Neurocomputing. 147, 1, p. 291-298 8 p.

    Research output: Contribution to journalArticle

  20. Published

    MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model

    Akusok, A., Veganzones, D., Miché, Y., Björk, K-M., du Jardin, P., Séverin, E. & Lendasse, A., 2015, In : Neurocomputing. 159, p. 242-250

    Research output: Contribution to journalArticle

  21. Published

    Minimal Learning Machine: A novel supervised distance-based approach for regression and classification

    de Souza Junior, A. H., Barreto, G., Corona, F., Barretto, G., Miche, Y. & Lendasse, A., 2015, In : Neurocomputing. 164, p. 3444

    Research output: Contribution to journalArticle

  22. Published

    Regional models: A new approach for nonlinear system identification via clustering of the self-organizing map

    Souza Junior, A. H., Barreto, G. A. & Corona, F., 2015, In : Neurocomputing. 147, p. 31-46

    Research output: Contribution to journalArticle

  23. Published

    Skeleton-based action recognition with extreme learning machines

    Chen, X. & Koskela, M., 2015, In : Neurocomputing. 149, Part A, p. 397-396

    Research output: Contribution to journalArticle

  24. Published

    SOM-ELM—Self-Organized Clustering using ELM

    Miché, Y., Akusok, A., Veganzones, D., Björk, K-M., Séverin, E., du Jardin, P., Termenón, M. & Lendasse, A., 2015, In : Neurocomputing. 165, p. 238254

    Research output: Contribution to journalArticle

  25. Published

    Towards cost-sensitive adaptation: when is it worth updating your predictive model?

    Zliobaite, I., Budka, M. & Stahl, F., 2015, In : Neurocomputing. 150, Part A, p. 240249

    Research output: Contribution to journalArticle

  26. Published

    Understanding emotional impact of images using Bayesian multiple kernel learning

    Zhang, H., Gönen, M., Yang, Z. & Oja, E., 2015, In : Neurocomputing. 165, 00, p. 3-13

    Research output: Contribution to journalArticle

  27. 2014
  28. Published

    Correlation-based embedding of pairwise score data

    Strickert, M., Bunte, K., Schleif, F. M. & Hüllermeier, E., 2 Oct 2014, In : Neurocomputing. 141, p. 97-109 13 p.

    Research output: Contribution to journalArticle

  29. Published

    Multi-task and multi-view learning of user state

    Kandemir, M., Vetek, A., Gönen, M., Klami, A. & Kaski, S., 2 Sep 2014, In : Neurocomputing. 139, p. 97-106 10 p.

    Research output: Contribution to journalArticle

  30. Published

    Advances in extreme learning machines (ELM2012)

    Lendasse, A., He, Q., Miche, Y. & Huang, G. B., 27 Mar 2014, In : Neurocomputing. 128, p. 1-3 3 p.

    Research output: Contribution to journalEditorial

  31. Published

    Adaptive multiplicative updates for quadratic nonnegative matrix factorization

    Zhang, H., Yang, Z. & Oja, E., 2014, In : Neurocomputing. 134, p. 206-213

    Research output: Contribution to journalArticle

  32. Published

    Bankruptcy prediction using Extreme Learning Machine and financial expertise

    Yu, Q., Miche, Y., Séverin, E. & Lendasse, A., 2014, In : Neurocomputing. 128, 128, p. 296-302

    Research output: Contribution to journalArticle

  33. Published

    Ensemble Delta Test- Extreme Learning Machine (DT-ELM) For Regression

    Yu, Q., van Heeswijk, M., Miche, Y., Nian, R., He, B., Séverin, E. & Lendasse, A., 2014, In : Neurocomputing. 129, p. 153-158

    Research output: Contribution to journalArticle

  34. Published

    Extreme learning machines for soybean classification in remote sensing hyperspectral images

    Moreno, R., Corona, F., Lendasse, A., Grana, M. & Galvao, L., 2014, In : Neurocomputing. 128, p. 207-216

    Research output: Contribution to journalArticle

  35. Published

    Extreme Learning Machine towards Dynamic Model Hypothesis in Fish Ethology Research

    Nian, R., He, B., Zheng, B., van Heeswijk, M., Yu, Q., Miche, Y. & Lendasse, A., 2014, In : Neurocomputing. 128, p. 273-284

    Research output: Contribution to journalArticle

  36. Published

    Mixture of Gaussians for distance estimation with missing data

    Eirola, E., Lendasse, A., Vandewalle, V. & Biernacki, C., 2014, In : Neurocomputing. 131, p. 32-42

    Research output: Contribution to journalArticle

  37. 2013
  38. Published

    Feature Selection for Nonlinear Models using Extreme Learning Machines

    Frénay, B., van Heeswijk, M., Miche, Y., Verleysen, M. & Lendasse, A., 2013, In : Neurocomputing. 102, p. 111-124

    Research output: Contribution to journalArticle

  39. Published

    Finding Dependent and Independent Components from Related Data Sets: A Generalized Canonical Correlation Based Method

    Karhunen, J., Hao, T. & Ylipaavalniemi, J., 2013, In : Neurocomputing. 113, p. 153-167

    Research output: Contribution to journalArticle

  40. Published

    Regularized Extreme Learning Machine For Regression with Missing Data

    Yu, Q., Miche, Y., Eirola, E., van Heeswijk, M., Séverin, E. & Lendasse, A., 2013, In : Neurocomputing. 102, p. 4551

    Research output: Contribution to journalArticle

  41. Published

    Transfer learning using a nonparametric sparse topic model

    Faisal, A., Gillberg, J., Leen, G. & Peltonen, J., 2013, In : Neurocomputing. 112, 0, p. 124-137

    Research output: Contribution to journalArticle

  42. 2012
  43. Published

    Adaptive kernel smoothing regression for spatio-temporal environmental datasets

    Montesino Pouzols, F. & Lendasse, A., 1 Aug 2012, In : Neurocomputing. 90, p. 59-65 7 p.

    Research output: Contribution to journalArticle

  44. Published

    Reinforcement learning based sensing policy optimization for energy efficient cognitive radio networks

    Oksanen, J., Lunden, J. & Koivunen, V., 2012, In : Neurocomputing. 80, 80, p. 102-110

    Research output: Contribution to journalArticle

  45. Published

    Three-way analysis of structural health monitoring data

    Prada, M. A. ., Toivola, J., Kullaa, J. & Hollmén, J., 2012, In : Neurocomputing. 80, p. 119-128

    Research output: Contribution to journalArticle

  46. 2011
  47. Published

    Parameter-insensitive kernel in extreme learning for non-linear support vector regression

    Frénay, B. & Verleysen, M., Sep 2011, In : Neurocomputing. 74, 16, p. 2526-2531 6 p.

    Research output: Contribution to journalArticle

  48. Published

    Fault tolerant machine learning for nanoscale cognitive radio

    Pajarinen, J., Peltonen, J. & Uusitalo, M. A., 2011, In : Neurocomputing. 74, 5, p. 753-764

    Research output: Contribution to journalArticle

  49. Published

    GPU-Accelerated and Parallelized ELM Ensembles for Large-scale Regression

    van Heeswijk, M., Miche, Y., Oja, E. & Lendasse, A., 2011, In : Neurocomputing. 74, 16, p. 2430-2437

    Research output: Contribution to journalArticle

  50. Published

    TROP-ELM: a Double-Regularized ELM using LARS and Tikhonov Regularization

    Miche, Y., van Heeswijk, M., Bas, P., Simula, O. & Lendasse, A., 2011, In : Neurocomputing. 74, 16, p. 2413-2421

    Research output: Contribution to journalArticle

  51. 2010
  52. Published

    Approximate k-NN Delta Test Minimization Method using Genetic Algorithms: Application to Time Series

    Mateo, F., Sovilj, D. & Gadea, R., 2010, In : Neurocomputing. 73, 10-12, p. 2017-2029

    Research output: Contribution to journalArticle

  53. Published

    Automatic clustering-based identification of autoregressive fuzzy inference models for time series

    Pouzols, F. M. & Barros, A. B., 2010, In : Neurocomputing. 73, 10-12, p. 1937-1949

    Research output: Contribution to journalArticle

  54. Published

    Automatic detection of onset and cessation of tree stem radius increase using dendrometer data

    Korpela, M., Mäkinen, H., Nöjd, P., Hollmén, J. & Sulkava, M., 2010, In : Neurocomputing. 73, 10-12, p. 2039-2046

    Research output: Contribution to journalArticle

  55. Published

    European Symposium on Times Series Prediction

    Lendasse, A., Honkela, T. & Simula, O., 2010, In : Neurocomputing. 73, 10-12, p. 1919-1922

    Research output: Contribution to journalArticle

  56. Published

    Multiple-Output Modelling for Multi-Step-Ahead Time Series Forecasting

    Taieb, S. B., Sorjamaa, A. & Bontempi, G., 2010, In : Neurocomputing. 73, 10-12, p. 1950-1957

    Research output: Contribution to journalArticle

  57. Published

    New method for instance or prototype selection using mutual information in time series prediction

    Guillén, A., Herrera, L., Rubio, G., Lendasse, A. & Pomares, H., 2010, In : Neurocomputing. 73, 10-12, p. 2030-2038

    Research output: Contribution to journalArticle

  58. Published

    OPELM and OPKNN in long-term prediction of time series using projected input data

    Sovilj, D., Sorjamaa, A., Yu, Q., Miche, Y. & Séverin, E., 2010, In : Neurocomputing. 73, 10-12, p. 1976-1986

    Research output: Contribution to journalArticle

  59. Published

    Transformations in variational Bayesian factor analysis to speed up learning

    Luttinen, J. & Ilin, A., 2010, In : Neurocomputing. 73, 7-9, p. 1093-1102

    Research output: Contribution to journalArticle

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