1. 2017
  2. Projected estimators for robust semi-supervised classification

    Krijthe, J. H. & Loog, M., 1 Jul 2017, In : Machine Learning. 106, 7, p. 993-1008 16 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. 2018
  4. A benchmark and comparison of active learning for logistic regression

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 83, p. 401-415 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  5. A spatio-temporal reference model of the aging brain

    huizinga, W., Poot, D., Vernooij, M. W., Roshchupkin, G. V., bron, E. E., Ikram, M. A., Rueckert, D., Niessen, W. & Klein, S., 2018, In : NeuroImage. 169, p. 11-22

    Research output: Contribution to journalArticleScientificpeer-review

  6. A variance maximization criterion for active learning

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 78, p. 358-370 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  7. Asymmetric kernel in Gaussian Processes for learning target variance

    Pintea, S. L., van Gemert, J. C. & Smeulders, A. W. M., 2018, In : Pattern Recognition Letters. 108, p. 70-77 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  8. Contextual loss functions for optimization of convolutional neural networks generating pseudo CTs from MRI

    van Stralen, M., Zhou, Y., Wozny, P. J., Seevinck, P. R. & Loog, M., 2018, Medical Imaging 2018: Image Processing. Angelini, E. D. & Landman, B. A. (eds.). Bellingham: SPIE, p. 105741N-1 - 105741N-6 6 p. 105741N. (Proceedings of Spie; vol. 10574).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  9. Effects of sampling skewness of the importance-weighted risk estimator on model selection

    Kouw, W. & Loog, M., 2018, 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, p. 1468-1473 6 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  10. Gradient descent for gaussian processes variance reduction

    Bottarelli, L. & Loog, M., 2018, Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Bai, X., Hancock, E. R., Ho, T. K., Wilson, R. C., Biggio, B. & Robles-Kelly, A. (eds.). Cham: Springer, p. 160-169 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11004 ).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  11. On domain-adaptive machine learning

    Kouw, W., 2018, 189 p.

    Research output: ThesisDissertation (TU Delft)

  12. Protein remote homology detection using dissimilarity-based multiple instance learning

    Mensi, A., Bicego, M., Lovato, P., Loog, M. & Tax, D. M. J., 2018, Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Bai, X., Hancock, E. R., Ho, T. K., Wilson, R. C., Biggio, B. & Robles-Kelly, A. (eds.). Cham: Springer, p. 119-129 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11004 ).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review