1. 2014
  2. Network guided group feature selection for classification of autism spectrum disorder

    Cheplygina, VV., Tax, DMJ., Loog, M. & Feragen, A., 2014, In : Lecture Notes in Computer Science. 8679, p. 1-8 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. Network-guided group feature selection for classification of autism spectrum disorder

    Cheplygina, VV., Tax, DMJ., Loog, M. & Feragen, A., 2014, Proceedings 5th International workshop MLMI 2014, held in conjunction with MICCAI 2014. Wu, G., Zhang, D. & Zhou, L. (eds.). Springer, p. 190-197 8 p. (Lecture Notes in Computer Science; vol. 8679).

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

  4. Semi-hidden target recognition in gated viewer images fused with thermal IR images

    Smeelen, MA., Schwering, PBW., Toet, A. & Loog, M., 2014, In : Information Fusion. 18, 1, p. 131-147 17 p.

    Research output: Contribution to journalArticleScientificpeer-review

  5. Semi-supervised linear discriminant analysis through moment-constraint parameter estimation

    Loog, M., 2014, In : Pattern Recognition Letters. 37, 1, p. 24-31 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  6. Towards scalable prototype selection by genetic algorithms with fast criteria

    Plasencia Calana, Y., Orozco Alzate, M., Mendez-Vasquez, H., García-Reyes, EB. & Duin, RPW., 2014, Proceedings of the Joint IAPR International Workshop, S+SSPR 2014. Fränti, P., Brown, G., Loog, M., Escolano, F. & Peilllo, M. (eds.). Berlin Heidelberg, Germany: Springer, p. 343-352 10 p. (Lecture Notes in Computer Science; vol. 8621).

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

  7. 2015
  8. Implicitly Constrained Semi-Supervised Least Squares Classification

    Krijthe, JH. & Loog, M., 2015, Proceedings of the 14th International Symposium on Advances in Intelligent Data Analysis XIV. Fromont, T., de Bie, T. & van Leeuwen, M. (eds.). Dordrecht: Springer, p. 158-169 12 p. (Lecture Notes in Computer Science; vol. 9385).

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

  9. Label stability in multiple instance learning

    Cheplygina, VV., Sørensen, L., Tax, DMJ., de Bruijne, M. & Loog, M., 2015, Proceedings - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention. Hornegger, J., Navab, N., Wells, WM. & Frangi, AF. (eds.). Cham: Springer, p. 539-546 8 p. (Lecture Notes in Computer Science; vol. 9349).

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

  10. Multiple instance learning with bag dissimilarities

    Cheplygina, VV., Tax, DMJ. & Loog, M., 2015, In : Pattern Recognition. 48, 1, p. 264-275 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

  11. On classification with bags, groups and sets

    Cheplygina, VV., Tax, DMJ. & Loog, M., 2015, In : Pattern Recognition Letters. 59, July, p. 11-17 7 p.

    Research output: Contribution to journalArticleScientificpeer-review

  12. Relevance sampling

    Nielsen, M., Markussen, B. & Loog, M., 2015, Proceedings of the 8ht Workshop on Information Theoretic Methods in Science and Engineering. Rissanen, J., Harremoes, P., Forchhammer, S., Roos, T. & Myllymaki, P. (eds.). Helsinki: University of Helsinki, p. 35-38 4 p.

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

  13. Semi-supervised nearest mean classification through a constrained log-likelihood

    Loog, M. & Jensen, AC., 2015, In : IEEE Transactions on Neural Networks. 26, 5, p. 995-1006 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

  14. Single- vs. multiple-instance classification

    Alpaydin, E., Cheplygina, VV., Loog, M. & Tax, DMJ., 2015, In : Pattern Recognition. 48, 9, p. 2831-2838 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  15. Training of templates for object recognition in invertible orientation scores: Application to optic nerve head detection in retinal images

    Bekkers, E., Duits, R. & Loog, M., 2015, Proceedings - 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition. Tai, XC., Bae, E., Chan, TF. & Lysaker, M. (eds.). Cham, Switzerland: Springer, p. 464-477 14 p. (Lecture Notes in Computer Science; vol. 8932).

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

  16. 2016
  17. A soft-labeled self-training approach

    Mey, A. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 2604-2609 6 p.

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

  18. Active Learning Using Uncertainty Information

    Yang, Y. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 2646-2651 6 p.

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

  19. An Empirical Investigation into the Inconsistency of Sequential Active Learning

    Loog, M. & Yang, Y., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 210-215 6 p.

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

  20. Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification

    Loog, M., 2016, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 38, 3, p. 462-475 14 p.

    Research output: Contribution to journalArticleScientificpeer-review

  21. Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings

    Carneiro, G. (ed.), Mateus, D. (ed.), Peter, L. (ed.), Bradley, A. (ed.), Tavares, J. M. R. S. (ed.), Belagiannis, V. (ed.), Papa, J. P. (ed.), Nascimento, J. C. (ed.), Loog, M. (ed.), Lu, Z. (ed.), Cardoso, J. S. (ed.) & Cornebise, J. (ed.), 2016, 1 ed. Springer. 280 p. (Lecture Notes in Computer Science: Image Processing, Computer Vision, Pattern Recognition, and Graphics; vol. 10008)

    Research output: Book/ReportBook editingScientificpeer-review

  22. Dissimilarity-based ensembles for multiple instance learning

    Cheplygina, VV., Tax, DMJ. & Loog, M., 2016, In : IEEE Transactions on Neural Networks and Learning Systems. 27, 6, p. 1379-1391 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  23. Early Experiences with Crowdsourcing Airway Annotations in Chest CT

    Cheplygina, V., Perez-Rovira, A., Kuo, W., Tiddens, H. A. W. M. & Bruijne, M. D., 2016, Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Proceedings. Carneiro, G., Mateus, D., Peter, L., Bradley, A., Tavares, J. M. R. S., Belagiannis, V., Papa, J. P., Nascimento, J. C., Loog, M., Lu, Z., Cardoso, J. S. & Cornebise, J. (eds.). Cham: Springer, p. 209-2018 10 p. (Lecture Notes in Computer Science; vol. 10008).

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

  24. Feature-Level Domain Adaptation

    Kouw, W., van der Maaten, L., Krijthe, J. & Loog, M., 2016, In : Journal of Machine Learning Research . 17, p. 1-32 32 p.

    Research output: Contribution to journalArticleScientificpeer-review

  25. Learning Algorithms for Digital Reconstruction of Van Gogh’s Drawings

    Zeng, Y., Tang, J., van der Lubbe, J. & Loog, M., 2016, EuroMed 2016 - 6th International Conference - Proceedings: Digital Heritage - Progress in Cultural Heritage: Documentation, Preservation, and Protection. Ioannides, M., Vink, E., Moropoulou, A., Hagedorn-Saupe, M., Fresa, A., Liestøl, G., Rajcic, V. & Grussenmeyer, P. (eds.). Cham: Springer, Vol. 1. p. 322-333 12 p. (Lecture Notes in Computer Science; vol. 10058).

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

  26. Modeling the brain morphology distribution in the general aging population

    Huizinga, W., Poot, D. H. J., Roshchupkin, G., Bron, E. E., Ikram, M. A., Vernooij, M. W., Rueckert, D., Niessen, W. J. & Klein, S., 2016, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. Gimi, B. & Krol, A. (eds.). SPIE, Vol. 9788. p. 1-7 97880I. (Proceedings of SPIE; vol. 9788).

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

  27. On Regularization Parameter Estimation under Covariate Shift

    Kouw, W. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 426-431 6 p.

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

  28. Optimistic semi-supervised least squares classification

    Krijthe, J. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). IEEE, p. 1677-1682 6 p.

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

  29. Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings

    Robles-Kelly, A. (ed.), Loog, M. (ed.), Biggio, B. (ed.), Escolano, F. (ed.) & Wilson, R. (ed.), 2016, Cham: Springer. 378 p. (Lecture Notes in Computer Science; vol. 10029)

    Research output: Book/ReportBook editingScientificpeer-review

  30. The Peaking Phenomenon in Semi-supervised Learning

    Krijthe, J. & Loog, M., 2016, Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2016, proceedings. Robles-Kelly, A., Loog, M., Biggio, B., Escolano, F. & Wilson, R. (eds.). Cham: Springer, p. 299-309 11 p. (Lecture Notes in Computer Science; vol. 10029).

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

  31. The Similarity Between Dissimilarities

    Tax, D., Cheplygina, V., Duin, B. & van de Poll, J., 2016, Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2016, proceedings. Robles-Kelly, A., Loog, M., Biggio, B., Escolano, F. & Wilson, R. (eds.). Cham: Springer, p. 84-94 11 p. (Lecture Notes in Computer Science; vol. 10029).

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

  32. Weighted K-Nearest Neighbor Revisited

    Bicego, M. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 1642-1647 6 p.

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

  33. 2017
  34. A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection

    Plasencia-Calaña, Y., Li, Y., Duin, R. P. W., Orozco-Alzate, M., Loog, M. & García-Reyes, E., 2017, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016, Proceedings. Beltrán-Castañón, C., Nyström, I. & Famili, F. (eds.). Cham: Springer, p. 150-157 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10125 LNCS).

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

  35. Define and Let Go: An Interview with John Habraken

    Havik, K. & Teerds, H., 2017, Facing Value: Radical Perspectives From The Arts. Lauwaert, M. & van Westrenen, F. (eds.). Valiz, p. 313-320

    Research output: Chapter in Book/Conference proceedings/Edited volumeChapterPopular

  36. Do you trust your multiple instance learning classifier?

    Cheplygina, V., Sørensen, L., Tax, D., de Bruijne, M. & Loog, M., 2017, p. 72-73. 2 p.

    Research output: Contribution to conferenceAbstractScientific

  37. Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision

    Wu, J., Bai, X., Loog, M., Roli, F. & Zhou, Z-H., 2017, In : Pattern Recognition. 71, p. 444-445 2 p.

    Research output: Contribution to journalEditorialScientific

  38. Generalization Bound Minimization for Active Learning

    Viering, T., Krijthe, J. & Loog, M., 2017, p. 108-109. 2 p.

    Research output: Contribution to conferenceAbstractScientific

  39. Over culturele referentiekaders en ankerpunten: Aantekeningen bij een semantische zoektocht in Nederland en Vlaanderen: Essay

    Avermaete, T., 2017, Frankfurt dialogen: Aanleidingen voor een gesprek over architectuur. Raats, M. (ed.). Rotterdam: Het Nieuwe Instituut, p. 92-118

    Research output: Chapter in Book/Conference proceedings/Edited volumeChapterProfessional

  40. Reproducible pattern recognition research: The case of optimistic SSL

    Krijthe, J. H. & Loog, M., 2017, Reproducible Research in Pattern Recognition: 1st International Workshop, RRPR 2016, Revised Selected Papers. Kerautret, B., Colom, M. & Monasse, P. (eds.). Cham: Springer, p. 48-59 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10214 ).

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

  41. Retorische terughoudendheid: Essay

    Rosbottom, D., 2017, Frankfurt dialogen: Aanleidingen voor een gesprek over architectuur. Raats, M. (ed.). Rotterdam: Het Nieuwe Instituut, p. 64-90

    Research output: Chapter in Book/Conference proceedings/Edited volumeChapterProfessional

  42. Robust semi-supervised least squares classification by implicit constraints

    Krijthe, J. & Loog, M., 2017, In : Pattern Recognition. 63, p. 115-126 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

  43. Supervised scale-regularized linear convolutionary filters

    Loog, M. & Lauze, F., 2017, British Machine Vision Conference 2017, BMVC 2017. BMVA Press, 11 p.

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

  44. The Infrastructure of Bare Life: Another Definition of Housing from and for the Global South

    Avermaete, T., 2017, Infrastructure Space. Ruby, I. & Ruby, A. (eds.). Berlin: Ruby Press, p. 250-263

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

  45. 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

  46. 2018
  47. 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

  48. 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

  49. 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

  50. 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

  51. 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

  52. 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

  53. 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

  54. On domain-adaptive machine learning

    Kouw, W., 2018, 189 p.

    Research output: ThesisDissertation (TU Delft)

  55. 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