Jesse H. Krijthe, Marco Loog (2017), Reproducible pattern recognition research: The case of optimistic SSL, B. Kerautret, M. Colom, P. Monasse (Eds.), In Reproducible Research in Pattern Recognition p.48-59, Springer.

Jesse Krijthe, Marco Loog (2017), Robust semi-supervised least squares classification by implicit constraints, In Pattern Recognition Volume 63 p.115-126.

Marco Loog, François Lauze (2017), Supervised scale-regularized linear convolutionary filters, In British Machine Vision Conference 2017, BMVC 2017.

Yazhou Yang, Marco Loog (2016), Active Learning Using Uncertainty Information, In 2016 23rd International Conference on Pattern Recognition (ICPR) p.2646-2651.

Marco Loog, Yazhou Yang (2016), An Empirical Investigation into the Inconsistency of Sequential Active Learning, In 2016 23rd International Conference on Pattern Recognition (ICPR) p.210-215.

Alexander Mey, Marco Loog (2016), A soft-labeled self-training approach, In 2016 23rd International Conference on Pattern Recognition (ICPR) p.2604-2609.

M Loog (2016), Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification, In IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 38 p.462-475.

G. Carneiro, D. Mateus, L. Peter, A. Bradley, J.M.R.S. Tavares, V. Belagiannis, J.P. Papa, J.C. Nascimento, Marco Loog, Z. Lu, J.S. Cardoso, J. Cornebise (Eds.) (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, Athens, Greece, October 21, 2016, Proceedings, Springer.

VV Cheplygina, DMJ Tax, M Loog (2016), Dissimilarity-based ensembles for multiple instance learning, In IEEE Transactions on Neural Networks and Learning Systems Volume 27 p.1379-1391.

Wouter Kouw, Laurens van der Maaten, Jesse Krijthe, Marco Loog (2016), Feature-Level Domain Adaptation, In Journal of Machine Learning Research Volume 17 p.1-32.