| 2026 | IDA | On Sample-Wise Strict Monotonicity with a Gradient Update. | O. Taylan Turan, Marco Loog, David M. J. Tax |
| 2025 | IDA | Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data. | Marco Loog, Jesse H. Krijthe, Manuele Bicego |
| 2023 | RECOMB | Percolate: An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response. | Soufiane Mourragui, Marco Loog, Mirrelijn M. van Nee, Mark A. van de Wiel, Marcel J. T. Reinders, Lodewyk F. A. Wessels |
| 2022 | CVPR | Enhancing Classifier Conservativeness and Robustness by Polynomiality. | Ziqi Wang, Marco Loog |
| 2022 | ECCV | Social Processes: Self-supervised Meta-learning Over Conversational Groups for Forecasting Nonverbal Social Cues. | Chirag Raman, Hayley Hung, Marco Loog |
| 2021 | AAAI | Consistency and Finite Sample Behavior of Binary Class Probability Estimation. | Alexander Mey, Marco Loog |
| 2020 | BMVC | Black Magic in Deep Learning: How Human Skill Impacts Network Training. | Kanav Anand, Ziqi Wang, Marco Loog, Jan van Gemert |
| 2020 | ICPR | Bayesian Active Learning for Maximal Information Gain on Model Parameters. | Kasra Arnavaz, Aasa Feragen, Oswin Krause, Marco Loog |
| 2020 | ICPR | Respecting Domain Relations: Hypothesis Invariance for Domain Generalization. | Ziqi Wang, Marco Loog, Jan van Gemert |
| 2020 | IDA | A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization. | Alexander Mey, Tom Julian Viering, Marco Loog |
| 2020 | IDA | Making Learners (More) Monotone. | Tom Julian Viering, Alexander Mey, Marco Loog |
| 2020 | UAI | Semi-supervised learning, causality, and the conditional cluster assumption. | Julius von Kgelgen, Alexander Mey, Marco Loog, Bernhard Schlkopf |
| 2020 | SSPR | Target Robust Discriminant Analysis. | Wouter M. Kouw, Marco Loog |
| 2019 | AISTATS | Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features. | Julius von Kgelgen, Alexander Mey, Marco Loog |
| 2019 | COLT | Open Problem: Monotonicity of Learning. | Tom J. Viering, Alexander Mey, Marco Loog |
| 2018 | ICPR | Effects of sampling skewness of the importance-weighted risk estimator on model selection. | Wouter M. Kouw, Marco Loog |
| 2018 | SSPR | Gradient Descent for Gaussian Processes Variance Reduction. | Lorenzo Bottarelli, Marco Loog |
| 2018 | SSPR | Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning. | Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M. J. Tax |
| 2017 | BMVC | Object-Extent Pooling for Weakly Supervised Single-Shot Localization. | Amogh Gudi, Nicolai van Rosmalen, Marco Loog, Jan C. van Gemert |
| 2017 | BMVC | Supervised Scale-Regularized Linear Convolutionary Filters. | Marco Loog, Franois Lauze |
| 2016 | CIARP | A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection. | Yenisel Plasencia Calana, Yan Li, Robert P. W. Duin, Mauricio Orozco-Alzate, Marco Loog, Edel B. Garca Reyes |
| 2016 | ICPR | Weighted K-Nearest Neighbor revisited. | Manuele Bicego, Marco Loog |
| 2016 | ICPR | On regularization parameter estimation under covariate shift. | Wouter M. Kouw, Marco Loog |
| 2016 | ICPR | Reproducible Pattern Recognition Research: The Case of Optimistic SSL. | Jesse H. Krijthe, Marco Loog |
| 2016 | ICPR | Optimistic semi-supervised least squares classification. | Jesse H. Krijthe, Marco Loog |
| 2016 | ICPR | An empirical investigation into the inconsistency of sequential active learning. | Marco Loog, Yazhou Yang |
| 2016 | ICPR | A soft-labeled self-training approach. | Alexander Mey, Marco Loog |
| 2016 | ICPR | Active learning using uncertainty information. | Yazhou Yang, Marco Loog |
| 2016 | SSPR | The Peaking Phenomenon in Semi-supervised Learning. | Jesse H. Krijthe, Marco Loog |
| 2015 | IDA | Implicitly Constrained Semi-supervised Least Squares Classification. | Jesse H. Krijthe, Marco Loog |
| 2015 | MICCAI | Label Stability in Multiple Instance Learning. | Veronika Cheplygina, Lauge Srensen, David M. J. Tax, Marleen de Bruijne, Marco Loog |
| 2014 | ICPR | Classification of COPD with Multiple Instance Learning. | Veronika Cheplygina, Lauge Srensen, David M. J. Tax, Jesper Johannes Holst Pedersen, Marco Loog, Marleen de Bruijne |
| 2014 | ICPR | Implicitly Constrained Semi-supervised Linear Discriminant Analysis. | Jesse H. Krijthe, Marco Loog |
| 2014 | MICCAI | Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder. | Veronika Cheplygina, David M. J. Tax, Marco Loog, Aasa Feragen |
| 2014 | SSPR | Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance. | Robert P. W. Duin, Manuele Bicego, Mauricio Orozco-Alzate, Sang-Woon Kim, Marco Loog |
| 2012 | ICPR | Does one rotten apple spoil the whole barrel? | Veronika Cheplygina, David M. J. Tax, Marco Loog |
| 2012 | ICPR | Metric learning by directly minimizing the k-NN training error. | Konstantin Chernoff, Marco Loog, Mads Nielsen |
| 2012 | ICPR | A study on semi-supervised dissimilarity representation. | Viet Cuong Dinh, Robert P. W. Duin, Marco Loog |
| 2012 | ICPR | Training data selection for cancer detection in multispectral endoscopy images. | Viet Cuong Dinh, Marco Loog, Raimund Leitner, Olga Rajadell, Robert P. W. Duin |
| 2012 | ICPR | Automated classification of local patches in colon histopathology. | Habil Kalkan, Marius Nap, Robert P. W. Duin, Marco Loog |
| 2012 | ICPR | Improving cross-validation based classifier selection using meta-learning. | Jesse H. Krijthe, Tin Kam Ho, Marco Loog |
| 2012 | ICPR | Combining multi-scale dissimilarities for image classification. | Yan Li, Robert P. W. Duin, Marco Loog |
| 2012 | ICPR | Scale-invariant sampling for supervised image segmentation. | Yan Li, Marco Loog |
| 2012 | MICCAI | Automated Colorectal Cancer Diagnosis for Whole-Slice Histopathology. | Habil Kalkan, Marius Nap, Robert P. W. Duin, Marco Loog |
| 2012 | SSPR | Class-Dependent Dissimilarity Measures for Multiple Instance Learning. | Veronika Cheplygina, David M. J. Tax, Marco Loog |
| 2012 | SSPR | Mode Seeking Clustering by KNN and Mean Shift Evaluated. | Robert P. W. Duin, Ana L. N. Fred, Marco Loog, Elzbieta Pekalska |
| 2012 | SSPR | The Dipping Phenomenon. | Marco Loog, Robert P. W. Duin |
| 2012 | SSPR | Constrained Log-Likelihood-Based Semi-supervised Linear Discriminant Analysis. | Marco Loog, Are Charles Jensen |
| 2010 | BMVC | Stratified Generalized Procrustes Analysis. | Adrien Bartoli, Daniel Pizarro, Marco Loog |
| 2010 | ICPR | Feature-Based Dissimilarity Space Classification. | Robert P. W. Duin, Marco Loog, Elzbieta Pekalska, David M. J. Tax |
| 2010 | MICCAI | A Texton-Based Approach for the Classification of Lung Parenchyma in CT Images. | Mehrdad J. Gangeh, Lauge Srensen, Saher B. Shaker, Mohamed S. Kamel, Marleen de Bruijne, Marco Loog |
| 2010 | MICCAI | Image Dissimilarity-Based Quantification of Lung Disease from CT. | Lauge Srensen, Marco Loog, Pechin Lo, Haseem Ashraf, Asger Dirksen, Robert P. W. Duin, Marleen de Bruijne |
| 2010 | SSPR | Dissimilarity-Based Multiple Instance Learning. | Lauge Srensen, Marco Loog, David M. J. Tax, Wan-Jui Lee, Marleen de Bruijne, Robert P. W. Duin |
| 2009 | CVPR | Dense iterative contextual pixel classification using Kriging. | Melanie Ganz, Marco Loog, Sami S. Brandt, Mads Nielsen |
| 2009 | CVPR | Bicycle chain shape models. | Stefan Sommer, Aditya Tatu, Chen Chen, D. R. Jurgensen, Marleen de Bruijne, Marco Loog, Mads Nielsen, Franois Lauze |
| 2007 | MICCAI | A Family of Principal Component Analyses for Dealing with Outliers. | Juan Eugenio Iglesias, Marleen de Bruijne, Marco Loog, Franois Lauze, Mads Nielsen |
| 2007 | MICCAI | Quantifying Effect-Specific Mammographic Density. | Jakob Raundahl, Marco Loog, Paola Pettersen, Mads Nielsen |
| 2006 | ECCV | Bony Structure Suppression in Chest Radiographs. | Marco Loog, Bram van Ginneken |
| 2006 | ICPR | Conditional Linear Discriminant Analysis. | Marco Loog |
| 2006 | ICPR | Local Discriminant Analysis. | Marco Loog, Dick de Ridder |
| 2006 | ICPR | Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis. | A. K. Qin, Ponnuthurai N. Suganthan, Marco Loog |
| 2006 | SSPR | Generic Blind Source Separation Using Second-Order Local Statistics. | Marco Loog |
| 2005 | AAAI | Enhanced Direct Linear Discriminant Analysis for Feature Extraction on High Dimensional Data. | A. K. Qin, S. Y. M. Shi, Ponnuthurai N. Suganthan, Marco Loog |
| 2004 | ECCV | Support Blob Machines. The Sparsification of Linear Scale Space. | Marco Loog |
| 2004 | ECCV | Dimensionality Reduction by Canonical Contextual Correlation Projections. | Marco Loog, Bram van Ginneken, Robert P. W. Duin |
| 2004 | ICPR | Integrating Automatic and Interactive Brain Tumor Segmentation. | Erik Dam, Marco Loog, Marloes M. J. Letteboer |
| 2004 | ICPR | Pixel Position Regression - Application to Medical Image Segmentation. | Bram van Ginneken, Marco Loog |
| 2004 | ICPR | Static Posterior Probability Fusion for Signal Detection: Applications in the Detection of Interstitial Diseases in Chest Radiographs. | Marco Loog, Bram van Ginneken |
| 2004 | ICPR | Local Fisher Embedding. | Dick de Ridder, Marco Loog, Marcel J. T. Reinders |
| 2003 | MICCAI | Multi-scale Nodule Detection in Chest Radiographs. | Arnold M. R. Schilham, Bram van Ginneken, Marco Loog |
| 2002 | ICPR | Supervised Segmentation by Iterated Contextual Pixel Classification. | Marco Loog, Bram van Ginneken |
| 2002 | SSPR | Non-iterative Heteroscedastic Linear Dimension Reduction for Two-Class Data. | Marco Loog, Robert P. W. Duin |
| 2000 | ICPR | Multi-Class Linear Feature Extraction by Nonlinear PCA. | Robert P. W. Duin, Marco Loog, Reinhold Haeb-Umbach |
| 2000 | Interspeech | Multi-class linear dimension reduction by generalized Fisher criteria. | Marco Loog, Reinhold Haeb-Umbach |
| 1999 | Interspeech | An investigation of cepstral parameterisations for large vocabulary speech recognition. | Reinhold Haeb-Umbach, Marco Loog |