Marco Loog

According to our database, Marco Loog authored at least 213 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

The Shape of Learning Curves: A Review.

Tom J. Viering, Marco Loog

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results.

Alexander Mey, Marco Loog

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Also for k-means: more data does not imply better performance.

Marco Loog, Jesse H. Krijthe, Manuele Bicego

Mach. Learn., 2023

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

Proceedings of the Research in Computational Molecular Biology, 2023

Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models.

Chirag Raman, Alec Nonnemaker, Amelia Villegas-Morcillo, Hayley Hung, Marco Loog

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Review of Nonconformity Measures for Conformal Prediction in Regression.

Yuko Kato, David M. J. Tax, Marco Loog

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2022

To Actively Initialize Active Learning.

Yazhou Yang, Marco Loog

Pattern Recognit., 2022

A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance.

Marco Loog, Tom J. Viering

CoRR, 2022

An Analysis of Abstracted Model-Based Reinforcement Learning.

Rolf A. N. Starre, Marco Loog, Frans A. Oliehoek

CoRR, 2022

On the reusability of samples in active learning.

Gijs van Tulder, Marco Loog

CoRR, 2022

Why Did This Model Forecast This Future? Closed-Form Temporal Saliency Towards Causal Explanations of Probabilistic Forecasts.

Chirag Raman, Hayley Hung, Marco Loog

CoRR, 2022

LCDB 1.0: An Extensive Learning Curves Database for Classification Tasks.

Felix Mohr, Tom J. Viering, Marco Loog, Jan N. van Rijn

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Social Processes: Self-supervised Meta-learning Over Conversational Groups for Forecasting Nonverbal Social Cues.

Chirag Raman, Hayley Hung, Marco Loog

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Enhancing Classifier Conservativeness and Robustness by Polynomiality.

Ziqi Wang, Marco Loog

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Model-Based Reinforcement Learning with State Abstraction: A Survey.

Rolf A. N. Starre, Marco Loog, Frans A. Oliehoek

Proceedings of the Artificial Intelligence and Machine Learning, 2022

A View on Model Misspecification in Uncertainty Quantification.

Yuko Kato, David M. J. Tax, Marco Loog

Proceedings of the Artificial Intelligence and Machine Learning, 2022

Explaining Two Strange Learning Curves.

Zhiyi Chen, Marco Loog, Jesse H. Krijthe

Proceedings of the Artificial Intelligence and Machine Learning, 2022

2021

Resolution Learning in Deep Convolutional Networks Using Scale-Space Theory.

Silvia L. Pintea, Nergis Tomen, Stanley F. Goes, Marco Loog, Jan C. van Gemert

IEEE Trans. Image Process., 2021

Robust domain-adaptive discriminant analysis.

Wouter M. Kouw, Marco Loog

Pattern Recognit. Lett., 2021

A Review of Domain Adaptation without Target Labels.

Wouter M. Kouw, Marco Loog

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Social Processes: Self-Supervised Forecasting of Nonverbal Cues in Social Conversations.

Chirag Raman, Hayley Hung, Marco Loog

CoRR, 2021

ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility.

Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert

Proceedings of the Reproducible Research in Pattern Recognition, 2021

Consistency and Finite Sample Behavior of Binary Class Probability Estimation.

Alexander Mey, Marco Loog

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Brief Prehistory of Double Descent.

Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax

CoRR, 2020

Semi-supervised learning, causality, and the conditional cluster assumption.

Julius von Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Target Robust Discriminant Analysis.

Wouter M. Kouw, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

Making Learners (More) Monotone.

Tom Julian Viering, Alexander Mey, Marco Loog

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization.

Alexander Mey, Tom Julian Viering, Marco Loog

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Respecting Domain Relations: Hypothesis Invariance for Domain Generalization.

Ziqi Wang, Marco Loog, Jan van Gemert

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Bayesian Active Learning for Maximal Information Gain on Model Parameters.

Kasra Arnavaz, Aasa Feragen, Oswin Krause, Marco Loog

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Black Magic in Deep Learning: How Human Skill Impacts Network Training.

Kanav Anand, Ziqi Wang, Marco Loog, Jan van Gemert

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

A dissimilarity-based multiple instance learning approach for protein remote homology detection.

Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M. J. Tax

Pattern Recognit. Lett., 2019

Gaussian process variance reduction by location selection.

Lorenzo Bottarelli, Marco Loog

Pattern Recognit. Lett., 2019

Single shot active learning using pseudo annotators.

Yazhou Yang, Marco Loog

Pattern Recognit., 2019

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

Yuan Zeng, Jan C. A. van der Lubbe, Marco Loog

Mach. Vis. Appl., 2019

Nuclear discrepancy for single-shot batch active learning.

Tom J. Viering, Jesse H. Krijthe, Marco Loog

Mach. Learn., 2019

Improvability Through Semi-Supervised Learning: A Survey of Theoretical Results.

Alexander Mey, Marco Loog

CoRR, 2019

How to Manipulate CNNs to Make Them Lie: the GradCAM Case.

Tom J. Viering, Ziqi Wang, Marco Loog, Elmar Eisemann

CoRR, 2019

A review of single-source unsupervised domain adaptation.

Wouter M. Kouw, Marco Loog

CoRR, 2019

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

Soufiane Mourragui, Marco Loog, Mark A. van de Wiel, Marcel J. T. Reinders, Lodewyk F. A. Wessels

Bioinform., 2019

On the Statistical Detection of Adversarial Instances over Encrypted Data.

Mina Sheikhalishahi, Majid Nateghizad, Fabio Martinelli, Zekeriya Erkin, Marco Loog

Proceedings of the Security and Trust Management - 15th International Workshop, 2019

Minimizers of the Empirical Risk and Risk Monotonicity.

Marco Loog, Tom J. Viering, Alexander Mey

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robust Importance-Weighted Cross-Validation Under Sample Selection Bias.

Wouter M. Kouw, Jesse H. Krijthe, Marco Loog

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Learning An Mr Acquisition-Invariant Representation Using Siamese Neural Networks.

Wouter M. Kouw, Marco Loog, Lambertus W. Bartels, Adriënne M. Mendrik

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Open Problem: Monotonicity of Learning.

Tom J. Viering, Alexander Mey, Marco Loog

Proceedings of the Conference on Learning Theory, 2019

Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features.

Julius von Kügelgen, Alexander Mey, Marco Loog

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

A benchmark and comparison of active learning for logistic regression.

Yazhou Yang, Marco Loog

Pattern Recognit., 2018

A variance maximization criterion for active learning.

Yazhou Yang, Marco Loog

Pattern Recognit., 2018

Template Matching via Densities on the Roto-Translation Group.

Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Learning an MR acquisition-invariant representation using Siamese neural networks.

Wouter M. Kouw, Marco Loog, Wilbert Bartels, Adriënne M. Mendrik

CoRR, 2018

Distance Based Source Domain Selection for Sentiment Classification.

Lex Razoux Schultz, Marco Loog, Peyman Mohajerin Esfahani

CoRR, 2018

Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features.

Julius von Kügelgen, Alexander Mey, Marco Loog

CoRR, 2018

Target Contrastive Pessimistic Discriminant Analysis.

Wouter M. Kouw, Marco Loog

CoRR, 2018

Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning.

Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M. J. Tax

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Gradient Descent for Gaussian Processes Variance Reduction.

Lorenzo Bottarelli, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Contextual loss functions for optimization of convolutional neural networks generating pseudo CTs from MRI.

Marijn van Stralen, Y. Zhou, P. J. Wozny, Peter R. Seevinck, Marco Loog

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Effects of sampling skewness of the importance-weighted risk estimator on model selection.

Wouter M. Kouw, Marco Loog

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

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

Jianxin Wu, Xiang Bai, Marco Loog, Fabio Roli, Zhi-Hua Zhou

Pattern Recognit., 2017

Robust semi-supervised least squares classification by implicit constraints.

Jesse H. Krijthe, Marco Loog

Pattern Recognit., 2017

Projected estimators for robust semi-supervised classification.

Jesse H. Krijthe, Marco Loog

Mach. Learn., 2017

Supervised Classification: Quite a Brief Overview.

Marco Loog

CoRR, 2017

On reducing sampling variance in covariate shift using control variates.

Wouter M. Kouw, Marco Loog

CoRR, 2017

MR Acquisition-Invariant Representation Learning.

Wouter M. Kouw, Marco Loog, Lambertus W. Bartels, Adriënne M. Mendrik

CoRR, 2017

Nuclear Discrepancy for Active Learning.

Tom J. Viering, Jesse H. Krijthe, Marco Loog

CoRR, 2017

Scale-Regularized Filter Learning.

Marco Loog, François Lauze

CoRR, 2017

On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL.

Marco Loog, Jesse H. Krijthe, Are Charles Jensen

CoRR, 2017

Target contrastive pessimistic risk for robust domain adaptation.

Wouter M. Kouw, Marco Loog

CoRR, 2017

Supervised Scale-Regularized Linear Convolutionary Filters.

Marco Loog, François Lauze

Proceedings of the British Machine Vision Conference 2017, 2017

Object-Extent Pooling for Weakly Supervised Single-Shot Localization.

Amogh Gudi, Nicolai van Rosmalen, Marco Loog, Jan C. van Gemert

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Dissimilarity-Based Ensembles for Multiple Instance Learning.

Veronika Cheplygina, David M. J. Tax, Marco Loog

IEEE Trans. Neural Networks Learn. Syst., 2016

Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification.

Marco Loog

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Feature-Level Domain Adaptation.

Wouter M. Kouw, Laurens J. P. van der Maaten, Jesse H. Krijthe, Marco Loog

J. Mach. Learn. Res., 2016

The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

CoRR, 2016

Template Matching on the Roto-Translation Group.

Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits

CoRR, 2016

The Peaking Phenomenon in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2016

Active learning using uncertainty information.

Yazhou Yang, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

A soft-labeled self-training approach.

Alexander Mey, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

An empirical investigation into the inconsistency of sequential active learning.

Marco Loog, Yazhou Yang

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Optimistic semi-supervised least squares classification.

Jesse H. Krijthe, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Reproducible Pattern Recognition Research: The Case of Optimistic SSL.

Jesse H. Krijthe, Marco Loog

Proceedings of the Reproducible Research in Pattern Recognition, 2016

On regularization parameter estimation under covariate shift.

Wouter M. Kouw, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Weighted K-Nearest Neighbor revisited.

Manuele Bicego, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Learning Algorithms for Digital Reconstruction of Van Gogh's Drawings.

Yuan Zeng, Jiexiong Tang, Jan C. A. van der Lubbe, Marco Loog

Proceedings of the Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection, 2016

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. García Reyes

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2016

On Measuring and Quantifying Performance: error rates, surrogate Loss, and an Example in Semi-Supervised Learning.

Marco Loog, Jesse H. Krijthe, Are Charles Jensen

Proceedings of the Handbook of Pattern Recognition and Computer Vision, 5th Ed., 2016

2015

Semi-Supervised Nearest Mean Classification Through a Constrained Log-Likelihood.

Marco Loog, Are Charles Jensen

IEEE Trans. Neural Networks Learn. Syst., 2015

On classification with bags, groups and sets.

Veronika Cheplygina, David M. J. Tax, Marco Loog

Pattern Recognit. Lett., 2015

Multiple instance learning with bag dissimilarities.

Veronika Cheplygina, David M. J. Tax, Marco Loog

Pattern Recognit., 2015

Single- vs. multiple-instance classification.

Ethem Alpaydin, Veronika Cheplygina, Marco Loog, David M. J. Tax

Pattern Recognit., 2015

Label Stability in Multiple Instance Learning.

Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Marleen de Bruijne, Marco Loog

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Implicitly Constrained Semi-supervised Least Squares Classification.

Jesse H. Krijthe, Marco Loog

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014

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

Marco Loog

Pattern Recognit. Lett., 2014

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

Menno A. Smeelen, Piet B. W. Schwering, Alexander Toet, Marco Loog

Inf. Fusion, 2014

Quantile Representation for Indirect Immunofluorescence Image Classification.

David M. J. Tax, Veronika Cheplygina, Marco Loog

CoRR, 2014

Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance.

Robert P. W. Duin, Manuele Bicego, Mauricio Orozco-Alzate, Sang-Woon Kim, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder.

Veronika Cheplygina, David M. J. Tax, Marco Loog, Aasa Feragen

Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

Implicitly Constrained Semi-supervised Linear Discriminant Analysis.

Jesse H. Krijthe, Marco Loog

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Classification of COPD with Multiple Instance Learning.

Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Jesper Johannes Holst Pedersen, Marco Loog, Marleen de Bruijne

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images.

Erik J. Bekkers, Remco Duits, Marco Loog

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2013

Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness.

Robert P. W. Duin, Elzbieta Pekalska, Marco Loog

Proceedings of the Similarity-Based Pattern Analysis and Recognition, 2013

Multi-spectral video endoscopy system for the detection of cancerous tissue.

Raimund Leitner, Martin De Biasio, Thomas Arnold, Viet Cuong Dinh, Marco Loog, Robert P. W. Duin

Pattern Recognit. Lett., 2013

Multiple-instance learning as a classifier combining problem.

Yan Li, David M. J. Tax, Robert P. W. Duin, Marco Loog

Pattern Recognit., 2013

FIDOS: A generalized Fisher based feature extraction method for domain shift.

Viet Cuong Dinh, Robert P. W. Duin, Ignacio Piqueras-Salazar, Marco Loog

Pattern Recognit., 2013

Stratified Generalized Procrustes Analysis.

Adrien Bartoli, Daniel Pizarro, Marco Loog

Int. J. Comput. Vis., 2013

On the Informativeness of Asymmetric Dissimilarities.

Yenisel Plasencia Calana, Veronika Cheplygina, Robert P. W. Duin, Edel B. García Reyes, Mauricio Orozco-Alzate, David M. J. Tax, Marco Loog

Proceedings of the Similarity-Based Pattern Recognition - Second International Workshop, 2013

Conditional Random Fields for Protein Function Prediction.

Thies Gehrmann, Marco Loog, Marcel J. T. Reinders, Dick de Ridder

Proceedings of the Pattern Recognition in Bioinformatics, 2013

The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples.

Yan Li, David M. J. Tax, Robert P. W. Duin, Marco Loog

Proceedings of the Multiple Classifier Systems, 11th International Workshop, 2013

Combining Instance Information to Classify Bags.

Veronika Cheplygina, David M. J. Tax, Marco Loog

Proceedings of the Multiple Classifier Systems, 11th International Workshop, 2013

Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification.

Adhish Prasoon, Christian Igel, Marco Loog, François Lauze, Erik B. Dam, Mads Nielsen

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012

Scale selection for supervised image segmentation.

Yan Li, David M. J. Tax, Marco Loog

Image Vis. Comput., 2012

Bridging Structure and Feature Representations in Graph Matching.

Wan-Jui Lee, Veronika Cheplygina, David M. J. Tax, Marco Loog, Robert P. W. Duin

Int. J. Pattern Recognit. Artif. Intell., 2012

Constrained Log-Likelihood-Based Semi-supervised Linear Discriminant Analysis.

Marco Loog, Are Charles Jensen

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

The Dipping Phenomenon.

Marco Loog, Robert P. W. Duin

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

Mode Seeking Clustering by KNN and Mean Shift Evaluated.

Robert P. W. Duin, Ana L. N. Fred, Marco Loog, Elzbieta Pekalska

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

Class-Dependent Dissimilarity Measures for Multiple Instance Learning.

Veronika Cheplygina, David M. J. Tax, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

Supervised localization of cell nuclei on TMA images.

Alessandro Ibba, Robert P. W. Duin, Marco Loog

Proceedings of the 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2012

Nearest neighbor-based importance weighting.

Marco Loog

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage.

Adhish Prasoon, Christian Igel, Marco Loog, François Lauze, Erik Dam, Mads Nielsen

Proceedings of the Medical Imaging 2012: Image Processing, 2012

Automated Colorectal Cancer Diagnosis for Whole-Slice Histopathology.

Habil Kalkan, Marius Nap, Robert P. W. Duin, Marco Loog

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Towards exaggerated emphysema stereotypes.

C. Chen, Lauge Sørensen, François Lauze, Christian Igel, Marco Loog, Aasa Feragen, Marleen de Bruijne, Mads Nielsen

Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012

Scale-invariant sampling for supervised image segmentation.

Yan Li, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Combining multi-scale dissimilarities for image classification.

Yan Li, Robert P. W. Duin, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Improving cross-validation based classifier selection using meta-learning.

Jesse H. Krijthe, Tin Kam Ho, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Automated classification of local patches in colon histopathology.

Habil Kalkan, Marius Nap, Robert P. W. Duin, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Training data selection for cancer detection in multispectral endoscopy images.

Viet Cuong Dinh, Marco Loog, Raimund Leitner, Olga Rajadell, Robert P. W. Duin

Proceedings of the 21st International Conference on Pattern Recognition, 2012

A study on semi-supervised dissimilarity representation.

Viet Cuong Dinh, Robert P. W. Duin, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Metric learning by directly minimizing the k-NN training error.

Konstantin Chernoff, Marco Loog, Mads Nielsen

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Does one rotten apple spoil the whole barrel?

Veronika Cheplygina, David M. J. Tax, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011

On Combining Computer-Aided Detection Systems.

Meindert Niemeijer, Marco Loog, Michael D. Abràmoff, Max A. Viergever, Mathias Prokop, Bram van Ginneken

IEEE Trans. Medical Imaging, 2011

SEDMI: Saliency based edge detection in multispectral images.

Viet Cuong Dinh, Raimund Leitner, Pavel Paclík, Marco Loog, Robert P. W. Duin

Image Vis. Comput., 2011

Dissimilarity-based detection of schizophrenia.

Aydin Ulas, Robert P. W. Duin, Umberto Castellani, Marco Loog, Pasquale Mirtuono, Manuele Bicego, Vittorio Murino, Marcella Bellani, Stefania Cerruti, Michele Tansella, Paolo Brambilla

Int. J. Imaging Syst. Technol., 2011

Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features.

Babak Loni, Gijs van Tulder, Pascal Wiggers, David M. J. Tax, Marco Loog

Proceedings of the Text, Speech and Dialogue - 14th International Conference, 2011

Bag Dissimilarities for Multiple Instance Learning.

David M. J. Tax, Marco Loog, Robert P. W. Duin, Veronika Cheplygina, Wan-Jui Lee

Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Forming Different-Complexity Covariance-Model Subspaces through Piecewise-Constant Spectra for Hyperspectral Image Classification.

Are Charles Jensen, Marco Loog

Proceedings of the Image Analysis - 17th Scandinavian Conference, 2011

Supervised Scale-Invariant Segmentation (and Detection).

Yan Li, David M. J. Tax, Marco Loog

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2011

Semi-supervised Linear Discriminant Analysis Using Moment Constraints.

Marco Loog

Proceedings of the Partially Supervised Learning - First IAPR TC3 Workshop, 2011

Generalized Augmentation of Multiple Kernels.

Wan-Jui Lee, Robert P. W. Duin, Marco Loog

Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

Information theoretic preattentive saliency: A closed-form solution.

Marco Loog

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Towards exaggerated image stereotypes.

Chen Chen, François Lauze, Christian Igel, Aasa Feragen, Marco Loog, Mads Nielsen

Proceedings of the First Asian Conference on Pattern Recognition, 2011

2010

Quantitative Comparison of Spot Detection Methods in Fluorescence Microscopy.

Ihor Smal, Marco Loog, Wiro J. Niessen, Erik Meijering

IEEE Trans. Medical Imaging, 2010

Using Multiscale Spectra in Regularizing Covariance Matrices for Hyperspectral Image Classification.

Are Charles Jensen, Marco Loog, Anne H. Schistad Solberg

IEEE Trans. Geosci. Remote. Sens., 2010

The Improbability of Harris Interest Points.

Marco Loog, François Lauze

IEEE Trans. Pattern Anal. Mach. Intell., 2010

A framework for optimizing measurement weight maps to minimize the required sample size.

Arish A. Qazi, Dan R. Jørgensen, Martin Lillholm, Marco Loog, Mads Nielsen, Erik B. Dam

Medical Image Anal., 2010

Dissimilarity-Based Multiple Instance Learning.

Lauge Sørensen, Marco Loog, David M. J. Tax, Wan-Jui Lee, Marleen de Bruijne, Robert P. W. Duin

Proceedings of the Structural, 2010

Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier.

Marco Loog

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Image Dissimilarity-Based Quantification of Lung Disease from CT.

Lauge Sørensen, Marco Loog, Pechin Lo, Haseem Ashraf, Asger Dirksen, Robert P. W. Duin, Marleen de Bruijne

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

A Texton-Based Approach for the Classification of Lung Parenchyma in CT Images.

Mehrdad J. Gangeh, Lauge Sørensen, Saher B. Shaker, Mohamed S. Kamel, Marleen de Bruijne, Marco Loog

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

Early diagnosis of dementia based on intersubject whole-brain dissimilarities.

Stefan Klein, Marco Loog, Fedde van der Lijn, Tom den Heijer, Alexander Hammers, Marleen de Bruijne, Aad van der Lugt, Robert P. W. Duin, Monique M. B. Breteler, Wiro J. Niessen

Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

Feature-Based Dissimilarity Space Classification.

Robert P. W. Duin, Marco Loog, Elzbieta Pekalska, David M. J. Tax

Proceedings of the Recognizing Patterns in Signals, Speech, Images and Videos, 2010

An experimental study on combining Euclidean distances.

Wan-Jui Lee, Robert P. W. Duin, Alessandro Ibba, Marco Loog

Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

2009

Optimal Mean-Precision Classifier.

David M. J. Tax, Marco Loog, Robert P. W. Duin

Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009

Maximum Membership Scale Selection.

Marco Loog, Yan Li, David M. J. Tax

Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009

Quantitative Comparison of Spot Detection Methods in Live-Cell Fluorescence Microscopy Imaging.

Ihor Smal, Marco Loog, Wiro J. Niessen, Erik Meijering

Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009

Discriminative Shape Alignment.

Marco Loog, Marleen de Bruijne

Proceedings of the Information Processing in Medical Imaging, 2009

Bicycle chain shape models.

Stefan Sommer, Aditya Tatu, Chen Chen, D. R. Jurgensen, Marleen de Bruijne, Marco Loog, Mads Nielsen, François Lauze

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009

Dense iterative contextual pixel classification using Kriging.

Melanie Ganz, Marco Loog, Sami S. Brandt, Mads Nielsen

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009

2008

Automated Effect-Specific Mammographic Pattern Measures.

Jakob Raundahl, Marco Loog, Paola Pettersen, László B. Tankó, Mads Nielsen

IEEE Trans. Medical Imaging, 2008

Efficient Segmentation by Sparse Pixel Classification.

Erik B. Dam, Marco Loog

IEEE Trans. Medical Imaging, 2008

On Distributional Assumptions and Whitened Cosine Similarities.

Marco Loog

IEEE Trans. Pattern Anal. Mach. Intell., 2008

Second Order Structure of Scale-Space Measurements.

Bo Markussen, Kim Steenstrup Pedersen, Marco Loog

J. Math. Imaging Vis., 2008

A note on an extreme case of the generalized optimal discriminant transformation.

Marco Loog, Xiaojun Wu, Jieping Lu, Jing-Yu Yang, Shitong Wang, Josef Kittler

Neurocomputing, 2008

A variational method for automatic localization of the most pathological ROI in the knee cartilage.

Arish A. Qazi, Erik B. Dam, Marco Loog, Mads Nielsen, François Lauze, Claus Christiansen

Proceedings of the Medical Imaging 2008: Image Processing, 2008

2007

On an alternative formulation of the Fisher criterion that overcomes the small sample problem.

Marco Loog

Pattern Recognit., 2007

Salient Point and Scale Detection by Minimum Likelihood.

Kim Steenstrup Pedersen, Marco Loog, Pieter van Dorst

Proceedings of the Gaussian Processes in Practice, 2007

A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion.

Marco Loog

J. Mach. Learn. Res., 2007

Generic Maximum Likely Scale Selection.

Kim Steenstrup Pedersen, Marco Loog, Bo Markussen

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2007

Blur Invariant Image Priors.

Marco Loog, François Lauze

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2007

The Jet Metric.

Marco Loog

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2007

Evaluation of four mammographic density measures on HRT data.

Jakob Raundahl, Marco Loog, Paola Pettersen, Mads Nielsen

Proceedings of the Medical Imaging 2007: Image Processing, 2007

Quantifying Effect-Specific Mammographic Density.

Jakob Raundahl, Marco Loog, Paola Pettersen, Mads Nielsen

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29, 2007

A Family of Principal Component Analyses for Dealing with Outliers.

Juan Eugenio Iglesias, Marleen de Bruijne, Marco Loog, François Lauze, Mads Nielsen

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29, 2007

Localized Maximum Entropy Shape Modelling.

Marco Loog

Proceedings of the Information Processing in Medical Imaging, 2007

2006

Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification.

Marco Loog, Bram van Ginneken

IEEE Trans. Medical Imaging, 2006

Recent submissions in linear dimensionality reduction and face recognition.

Robert P. W. Duin, Marco Loog, Tin Kam Ho

Pattern Recognit. Lett., 2006

Generalized null space uncorrelated Fisher discriminant analysis for linear dimensionality reduction.

A. Kai Qin, Ponnuthurai N. Suganthan, Marco Loog

Pattern Recognit., 2006

A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database.

Arnold M. R. Schilham, Bram van Ginneken, Marco Loog

Medical Image Anal., 2006

Filter learning: Application to suppression of bony structures from chest radiographs.

Marco Loog, Bram van Ginneken, Arnold M. R. Schilham

Medical Image Anal., 2006

Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database.

Bram van Ginneken, Mikkel B. Stegmann, Marco Loog

Medical Image Anal., 2006

Generic Blind Source Separation Using Second-Order Local Statistics.

Marco Loog

Proceedings of the Structural, 2006

Mammographic density measured as changes in tissue structure caused by HRT.

Jakob Raundahl, Marco Loog, Mads Nielsen

Proceedings of the Medical Imaging 2006: Image Processing, 2006

Understanding Hessian-Based Density Scoring.

Jakob Raundahl, Marco Loog, Mads Nielsen

Proceedings of the Digital Mammography, 2006

Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis.

A. Kai Qin, Ponnuthurai N. Suganthan, Marco Loog

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Local Discriminant Analysis.

Marco Loog, Dick de Ridder

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Conditional Linear Discriminant Analysis.

Marco Loog

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Bony Structure Suppression in Chest Radiographs.

Marco Loog, Bram van Ginneken

Proceedings of the Computer Vision Approaches to Medical Image Analysis, 2006

2005

Uncorrelated heteroscedastic LDA based on the weighted pairwise Chernoff criterion.

A. Kai Qin, Ponnuthurai N. Suganthan, Marco Loog

Pattern Recognit., 2005

Dimensionality reduction of image features using the canonical contextual correlation projection.

Marco Loog, Bram van Ginneken, Robert P. W. Duin

Pattern Recognit., 2005

A Scale Invariant Covariance Structure on Jet Space.

Bo Markussen, Kim Steenstrup Pedersen, Marco Loog

Proceedings of the Deep Structure, 2005

Maximum Likely Scale Estimation.

Marco Loog, Kim Steenstrup Pedersen, Bo Markussen

Proceedings of the Deep Structure, 2005

Enhanced Direct Linear Discriminant Analysis for Feature Extraction on High Dimensional Data.

A. Kai Qin, S. Y. M. Shi, Ponnuthurai N. Suganthan, Marco Loog

Proceedings of the Proceedings, 2005

2004

Supervised dimensionality reduction and contextual pattern recognition in medical image processing.

Marco Loog

PhD thesis, 2004

Linear Dimensionality Reduction via a Heteroscedastic Extension of LDA: The Chernoff Criterion.

Marco Loog, Robert P. W. Duin

IEEE Trans. Pattern Anal. Mach. Intell., 2004

The MDF discrimination measure: Fisher in disguise.

Marco Loog, Robert P. W. Duin, Max A. Viergever

Neural Networks, 2004

Comparative study of retinal vessel segmentation methods on a new publicly available database.

Meindert Niemeijer, Joes Staal, Bram van Ginneken, Marco Loog, Michael D. Abràmoff

Proceedings of the Medical Imaging 2004: Image Processing, 2004

Local Fisher Embedding.

Dick de Ridder, Marco Loog, Marcel J. T. Reinders

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Static Posterior Probability Fusion for Signal Detection: Applications in the Detection of Interstitial Diseases in Chest Radiographs.

Marco Loog, Bram van Ginneken

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Pixel Position Regression - Application to Medical Image Segmentation.

Bram van Ginneken, Marco Loog

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Integrating Automatic and Interactive Brain Tumor Segmentation.

Erik Dam, Marco Loog, Marloes M. J. Letteboer

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Dimensionality Reduction by Canonical Contextual Correlation Projections.

Marco Loog, Bram van Ginneken, Robert P. W. Duin

Proceedings of the Computer Vision, 2004

Support Blob Machines. The Sparsification of Linear Scale Space.

Marco Loog

Proceedings of the Computer Vision, 2004

2003

Gaussian Scale Space from Insufficient Image Information.

Marco Loog, Martin Lillholm, Mads Nielsen, Max A. Viergever

Proceedings of the Scale Space Methods in Computer Vision, 4th International Conference, 2003

Segmenting the posterior ribs in chest radiographs by iterated contextual pixel classification.

Marco Loog, Bram van Ginneken, Max A. Viergever

Proceedings of the Medical Imaging 2003: Image Processing, 2003

Interactive shape models.

Bram van Ginneken, Marleen de Bruijne, Marco Loog, Max A. Viergever

Proceedings of the Medical Imaging 2003: Image Processing, 2003

Model-based segmentation of abdominal aortic aneurysms in CTA images.

Marleen de Bruijne, Bram van Ginneken, Wiro J. Niessen, Marco Loog, Max A. Viergever

Proceedings of the Medical Imaging 2003: Image Processing, 2003

Multi-scale Nodule Detection in Chest Radiographs.

Arnold M. R. Schilham, Bram van Ginneken, Marco Loog

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2003

2002

Non-iterative Heteroscedastic Linear Dimension Reduction for Two-Class Data.

Marco Loog, Robert P. W. Duin

Proceedings of the Structural, 2002

Supervised Segmentation by Iterated Contextual Pixel Classification.

Marco Loog, Bram van Ginneken

Proceedings of the 16th International Conference on Pattern Recognition, 2002

2001

Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria.

Marco Loog, Robert P. W. Duin, Reinhold Haeb-Umbach

IEEE Trans. Pattern Anal. Mach. Intell., 2001

On the Behavior of Spatial Critical Points under Gaussian Blurring. A Folklore Theorem and Scale-Space Constraints.

Marco Loog, Johannes Jisse Duistermaat, Luc Florack

Proceedings of the Scale-Space and Morphology in Computer Vision, 2001

2000

Multi-class linear dimension reduction by generalized Fisher criteria.

Marco Loog, Reinhold Haeb-Umbach

Proceedings of the Sixth International Conference on Spoken Language Processing, 2000

Multi-Class Linear Feature Extraction by Nonlinear PCA.

Robert P. W. Duin, Marco Loog, Reinhold Haeb-Umbach

Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999

An investigation of cepstral parameterisations for large vocabulary speech recognition.

Reinhold Haeb-Umbach, Marco Loog

Proceedings of the Sixth European Conference on Speech Communication and Technology, 1999