Pierre Geurts

According to our database1, Pierre Geurts authored at least 76 papers between 2000 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology.
IEEE J. Biomed. Health Informatics, 2021

2020
Error curves for evaluating the quality of feature rankings.
PeerJ Comput. Sci., 2020

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2020

On the Transferability of Winning Tickets in Non-Natural Image Datasets.
CoRR, 2020

The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Nets Versus Trees for Feature Ranking and Gene Network Inference.
Proceedings of the Discovery Science - 23rd International Conference, 2020

2019
Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms.
CoRR, 2019

Gradient tree boosting with random output projections for multi-label classification and multi-output regression.
CoRR, 2019

Deep Quality-Value (DQV) Learning.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018
Global multi-output decision trees for interaction prediction.
Mach. Learn., 2018

Deep Transfer Learning for Art Classification Problems.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Comparison of Deep Transfer Learning Strategies for Digital Pathology.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

Random Subspace with Trees for Feature Selection Under Memory Constraints.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Automated Multimodal Volume Registration based on Supervised 3D Anatomical Landmark Detection.
Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP, Porto, Portugal, February 27, 2017

Tree ensemble methods and parcelling to identify brain areas related to Alzheimer's disease.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017

Globally Induced Forest: A Prepruning Compression Scheme.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2017

2016
Towards generic image classification using tree-based learning: An extensive empirical study.
Pattern Recognit. Lett., 2016

Collaborative analysis of multi-gigapixel imaging data using Cytomine.
Bioinform., 2016

Context-dependent feature analysis with random forests.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015
Rating Network Paths for Locality-Aware Overlay Construction and Routing.
IEEE/ACM Trans. Netw., 2015

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge.
IEEE Trans. Medical Imaging, 2015

2014
Classifying pairs with trees for supervised biological network inference.
CoRR, 2014

Random Forests with Random Projections of the Output Space for High Dimensional Multi-label Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging.
Proceedings of the Neural Connectomics Workshop at ECML 2014, 2014

2013
DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction.
IEEE/ACM Trans. Netw., 2013

Understanding variable importances in forests of randomized trees.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Ordinal Rating of Network Performance and Inference by Matrix Completion
CoRR, 2012

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery.
Bioinform., 2012

Embedding Monte Carlo Search of Features in Tree-Based Ensemble Methods.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Ensembles on Random Patches.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

L1-based compression of random forest models.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Comparator selection for RPC with many labels.
Proceedings of the ECAI 2012, 2012

2011
Learning to rank with extremely randomized trees.
Proceedings of the Yahoo! Learning to Rank Challenge, 2011

Learning from positive and unlabeled examples by enforcing statistical significance.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Automatic Localization of Interest Points in Zebrafish Images with Tree-Based Methods.
Proceedings of the Pattern Recognition in Bioinformatics, 2011

Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Decentralized prediction of end-to-end network performance classes.
Proceedings of the 2011 Conference on Emerging Networking Experiments and Technologies, 2011

2010
Bias vs Variance Decomposition for Regression and Classification.
Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

Enhancement of TCP over wired/wireless networks with packet loss classifiers inferred by supervised learning.
Wirel. Networks, 2010

Preface.
Proceedings of the third International Workshop on Machine Learning in Systems Biology, 2010

Network Distance Prediction Based on Decentralized Matrix Factorization.
Proceedings of the NETWORKING 2010, 2010

Incremental indexing and distributed image search using shared randomized vocabularies.
Proceedings of the 11th ACM SIGMM International Conference on Multimedia Information Retrieval, 2010

Biomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments.
Proceedings of the CLEF 2010 LABs and Workshops, 2010

2009
Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees.
IPSJ Trans. Comput. Vis. Appl., 2009

Fast Multi-class Image Annotation with Random Subwindows and Multiple Output Randomized Trees.
Proceedings of the VISAPP 2009 - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications, Lisboa, Portugal, February 5-8, 2009, 2009

Detecting Triangle Inequality Violations in Internet Coordinate Systems by Supervised Learning.
Proceedings of the NETWORKING 2009, 2009

A machine learning approach for material detection in hyperspectral images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009

2008
Exploiting tree-based variable importances to selectively identify relevant variables.
Proceedings of the Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery, 2008

2007
Estimation of rotor angles of synchronous machines using artificial neural networks and local PMU-based quantities.
Neurocomputing, 2007

Machine-learnt versus analytical models of TCP throughput.
Comput. Networks, 2007

Inferring biological networks with output kernel trees.
BMC Bioinform., 2007

Gradient boosting for kernelized output spaces.
Proceedings of the Machine Learning, 2007

2006
Extremely randomized trees.
Mach. Learn., 2006

On the Accuracy of Analytical Models of TCP Throughput.
Proceedings of the NETWORKING 2006, 2006

A Semi-Algebraic Description of Naive Bayes Models with Two Hidden Classes.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

Kernelizing the output of tree-based methods.
Proceedings of the Machine Learning, 2006

Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data.
Proceedings of the ESANN 2006, 2006

2005
Tree-Based Batch Mode Reinforcement Learning.
J. Mach. Learn. Res., 2005

Proteomic mass spectra classification using decision tree based ensemble methods.
Bioinform., 2005

Segment and Combine Approach for Non-parametric Time-Series Classification.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Improving TCP in Wireless Networks with an Adaptive Machine-Learnt Classifier of Packet Loss Causes.
Proceedings of the NETWORKING 2005: Networking Technologies, 2005

Closed-form dual perturb and combine for tree-based models.
Proceedings of the Machine Learning, 2005

Random Subwindows for Robust Image Classification.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Biomedical Image Classification with Random Subwindows and Decision Trees.
Proceedings of the Computer Vision for Biomedical Image Applications, 2005

Segment and Combine Approach for Biological Sequence Classification.
Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005

Bias vs. Variance Decomposition for Regression and Classification.
Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

2004
A Machine Learning Approach to Improve Congestion Control over Wireless Computer Networks.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

2003
A Comparison of Generic Machine Learning Algorithms for Image Classification.
Proceedings of the Research and Development in Intelligent Systems XX, 2003

Iteratively Extending Time Horizon Reinforcement Learning.
Proceedings of the Machine Learning: ECML 2003, 2003

2001
Pattern Extraction for Time Series Classification.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2001

Dual perturb and combine algorithm.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
Temporal Machine Learning for Switching Control.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

Some Enhencements of Decision Tree Bagging.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

Investigation and Reduction of Discretization Variance in Decision Tree Induction.
Proceedings of the Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31, 2000


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