papers

• Estimating the Effect of Early Treatment Initiation in Parkinson's Disease Using Observational Data
  
  Van den Heuvel, L., Evers, L.J., Meinders, M.J., Post, B., Stiggelbout, A.M., Heskes, T.M., Bloem, B.R. and Krijthe, J.H.
  Movement Disorders, 36: 407-414 (2021) - DOI - Code
• Density of Patient-Sharing Networks: Impact on the Value of Parkinson Care
  
  Vlaanderen, F., de Man, Y., Tanke, M., Munneke, M., Atsma, F., Meinders, M., Jeurissen, P., Bloem, B., Krijthe, J.H., Groenewoud, S.
  International Journal of Health Policy and Management, in press (2021) - PDF
• A brief prehistory of double descent
  
  Marco Loog, Tom Viering, Alexander Mey, Jesse H. Krijthe, and David M. J. Tax
  Proceedings of the National Academy of Sciences May 2020, 117 (20) 10625-10626 (2020) - DOI - arXiv
• Robust importance-weighted cross-validation under sample selection bias
  
  Wouter M. Kouw, Jesse H. Krijthe and Marco Loog
  International Workshop on Machine Learning for Signal Processing (2019) - DOI - arXiv
• Nuclear discrepancy for single-shot batch active learning
  
  Tom J. Viering, Jesse H. Krijthe and Marco Loog
  Machine Learning, 108 (8), pp. 1561-1599 (2019) - DOI - arXiv
• Measuring Parkinson's disease over time: The real-world within-subject reliability of the MDS-UPDRS
  
  Luc J.W. Evers, Jesse H. Krijthe, Marjan J. Meinders, Bastiaan R. Bloem and Tom M. Heskes
  Movement Disorders, 34: 1480-1487 (2019) - DOI
• Sex-Specific Patient Journeys in Early Parkinson's Disease in the Netherlands
  
  Floris P. Vlaanderen, Yvonne de Man, Jesse H. Krijthe, Marit A.C. Tanke, A.S. Groenewoud, Patrick P.T. Jeurissen, Sabine Oertelt-Prigione, Marten Munneke, Bastiaan R. Bloem and Marjan J.Meinders
  Frontiers in Neurology, 10, 794 (2019) - DOI
• Robust Semi-supervised Learning: Projections, Limits & Contraints
  
  Jesse H. Krijthe
  PhD Thesis - PDF - Code
• The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning
  
  Jesse H. Krijthe and Marco Loog
  Advances in Neural Information Processing Systems 31, 1790-1799 (2018) - arXiv
• Projected Estimators for Robust Semi-supervised Classification
  
  Jesse H. Krijthe and Marco Loog
  Machine Learning, 106 (7), 993–1008. (2017) - DOI - arXiv - Code
• Robust Semi-supervised Least Squares Classification by Implicit Constraints
  
  Jesse H. Krijthe and Marco Loog
  Pattern Recognition, 63, 115–126. (2017) - DOI - arXiv - Code
• The Peaking Phenomenon in Semi-supervised Learning
  
  Jesse H. Krijthe and Marco Loog
  Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) (LNCS, volume 10029), pp 299-309. - DOI - arXiv - Code
• Optimistic Semi-supervised Least Squares Classification
  
  Jesse H. Krijthe and Marco Loog
  Proceedings of the International Conference on Pattern Recognition (2016) - DOI - arXiv - Code
• Reproducible Pattern Recognition Research: The Case of Optimistic SSL
  
  Jesse H. Krijthe and Marco Loog
  RRPR 2016: 1st Workshop on Reproducible Research in Pattern Recognition - DOI - arXiv - Code
• RSSL: Semi-supervised Learning in R
  
  Jesse H. Krijthe
  RRPR 2016: 1st Workshop on Reproducible Research in Pattern Recognition - DOI - arXiv - Code
• Feature-Level Domain Adaptation
  
  Wouter M. Kouw, Laurens J.P. van der Maaten, Jesse H. Krijthe and Marco Loog
  Journal of Machine Learning Research, 17(171), 1-32 (2016) - PDF - arXiv - Code
• Pan-cancer subtyping in a 2D-map shows substructures that are driven by specific combinations of molecular characteristics
  
  Erdogan Taskesen, Sjoerd M. H. Huisman, Ahmed Mahfouz, Jesse H. Krijthe, Jeroen de Ridder, Anja van de Stolpe, Erik van den Akker, Wim Verheagh, Marcel J. T. Reinders
  Scientific Reports, 6, 24949 (2016) - DOI
• Implicitly Constrained Semi-Supervised Least Squares Classification
  
  Jesse H. Krijthe and Marco Loog
  The Fourteenth International Symposium on Intelligent Data Analysis (2015) - DOI - arXiv - Code
• Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
  
  Jesse H. Krijthe and Marco Loog
  Proceedings of the International Conference on Pattern Recognition (2014) - DOI - arXiv - Code
• Improving cross-validation based classifier selection using meta-learning
  
  Jesse H. Krijthe, Tin Kam Ho and Marco Loog
  Proceedings of the International Conference on Pattern Recognition (2012) - PDF - Code

presentations

• RSSL: Semi-Supervised Learning in R
  
  Jesse H. Krijthe
  useR! 2015 - Abstract - Poster - Code
• Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
  
  Jesse H. Krijthe and Marco Loog
  Benelearn 2015 - Abstract - Poster
• Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
  
  Jesse H. Krijthe and Marco Loog
  SSN Symposium 2015 - Abstract - Poster
• Robust Semi-Supervised Learning through Implicit Constraints
  
  Jesse H. Krijthe and Marco Loog
  Benelearn 2014 - Abstract - Slides
• Implicitly Constrained Least Squares Classification
  
  Jesse H. Krijthe and Marco Loog
  Machine Learning Summer School 2014 - Poster
• Improving Cross-Validation Classifier Selection Accuracy through Meta-learning
  
  Jesse Krijthe, Tin Kam Ho and Marco Loog
  Benelearn 2013 - Abstract - Slides