1. 2019
  2. On the Statistical Detection of Adversarial Instances over Encrypted Data

    Sheikhalishahi, M., Nateghizad, M., Martinelli, F., Erkin, Z. & Loog, M., 2019, Security and Trust Management - 15th International Workshop, STM 2019, Proceedings. Mauw, S. & Conti, M. (eds.). Springer, p. 71-88 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11738 LNCS).

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

  3. PRECISE: A domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors

    Mourragui, S., Loog, M., van der Wiel, M. A., Reinders, M. & Wessels, L., 2019, In : Bioinformatics. 35, 14, p. i510-i519 10 p., btz372.

    Research output: Contribution to journalArticleScientificpeer-review

  4. Robust Importance-Weighted Cross-Validation under Sample Selection Bias

    Kouw, W. M., Krijthe, J. H. & Loog, M., 2019, 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP). Piscataway: IEEE, p. 1-6 6 p. 8918731

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

  5. Single shot active learning using pseudo annotators

    Yang, Y. & Loog, M., 2019, In : Pattern Recognition. 89, p. 22-31 10 p.

    Research output: Contribution to journalArticleScientificpeer-review

  6. Multi-scale convolutional neural network for pixel-wise reconstruction of Van Gogh’s drawings

    Zeng, Y., van der Lubbe, J. C. A. & Loog, M., 1 Oct 2019, In : Machine Vision and Applications. 30, 7-8, p. 1229-1241 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  7. 2020
  8. A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization

    Mey, A., Viering, T. J. & Loog, M., 2020, Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Proceedings. Berthold, M. R., Feelders, A. & Krempl, G. (eds.). Springer Open, p. 326-338 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12080 LNCS).

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

  9. Assumptions & Expectations in Semi-Supervised Machine Learning

    Mey, A., 2020, 117 p.

    Research output: ThesisDissertation (TU Delft)

  10. Making Learners (More) Monotone

    Viering, T. J., Mey, A. & Loog, M., 2020, Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Proceedings. Berthold, M. R., Feelders, A. & Krempl, G. (eds.). Cham: Springer Open, p. 535-547 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12080 ).

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

  11. Semi-generative modelling: Covariate-shift adaptation with cause and effect features

    von Kügelgen, J., Mey, A. & Loog, M., 2020, In : Proceedings of Machine Learning Research. 89, 9 p.

    Research output: Contribution to journalConference articleScientificpeer-review

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