Pierre Geurts - RankMe

109 papers A* 6A 6B 12C 1Journal 41Unranked 37

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting. Mach. Learn. Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts
2024	J	`jnl`	Can local explanation techniques explain linear additive models? Data Min. Knowl. Discov. Amir Hossein Akhavan Rahnama, Judith Bütepage, Pierre Geurts, Henrik Boström
2024	—	`conf`	Faithfulness of Local Explanations for Tree-Based Ensemble Models. DS (2) Amir Hossein Akhavan Rahnama, Pierre Geurts, Henrik Boström
2024	J	`jnl`	Optimizing model-agnostic random subspace ensembles. Mach. Learn. Vân Anh Huynh-Thu, Pierre Geurts
2024	J	`jnl`	Parallelizing Autoregressive Generation with Variational State Space Models. CoRR Gaspard Lambrechts, Yann Claes, Pierre Geurts, Damien Ernst
2024	B	`conf`	Trust in Artificial Intelligence: Beyond Interpretability. ESANN Tassadit Bouadi, Benoît Frénay, Luis Galárraga, Pierre Geurts, Barbara Hammer, Gilles Perrouin
2023	J	`jnl`	Knowledge-Guided Additive Modeling For Supervised Regression. CoRR Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts
2023	B	`conf`	Knowledge-Guided Additive Modeling for Supervised Regression. DS Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts
2022	J	`jnl`	Distillation from heterogeneous unlabeled collections. CoRR Jean-Michel Begon, Pierre Geurts
2022	—	`conf`	Empirical Evaluation of Deep Learning Approaches for Landmark Detection in Fish Bioimages. ECCV Workshops (4) Navdeep Kumar, Claudia Di Biagio, Zachary Dellacqua, Ratish Raman, Arianna Martini, Clara Boglione, Marc Muller, Pierre Geurts, Raphaël Marée
2022	—	`conf`	Relieving Pixel-Wise Labeling Effort for Pathology Image Segmentation with Self-training. ECCV Workshops (7) Romain Mormont, Mehdi Testouri, Raphaël Marée, Pierre Geurts
2021	J	`jnl`	Advances in Digital Music Iconography: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain. Digit. Humanit. Q. Matthia Sabatelli, Nikolay Banar, Marie Cocriamont, Eva Coudyzer, Karine Lasaracina, Walter Daelemans, Pierre Geurts, Mike Kestemont
2021	—	`conf`	Deep Learning Approaches for Head and Operculum Segmentation in Zebrafish Microscopy Images. CAIP (1) Navdeep Kumar, Alessio Carletti, Paulo Jorge Gavaia, Marc Muller, M. Leonor Cancela, Pierre Geurts, Raphaël Marée
2021	J	`jnl`	Evaluation of Local Model-Agnostic Explanations Using Ground Truth. CoRR Amir Hossein Akhavan Rahnama, Judith Bütepage, Pierre Geurts, Henrik Boström
2021	A*	`conf`	From global to local MDI variable importances for random forests and when they are Shapley values. NeurIPS Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2021	J	`jnl`	From global to local MDI variable importances for random forests and when they are Shapley values. CoRR Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2021	J	`jnl`	Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology. IEEE J. Biomed. Health Informatics Romain Mormont, Pierre Geurts, Raphaël Marée
2021	J	`jnl`	On The Transferability of Deep-Q Networks. CoRR Matthia Sabatelli, Pierre Geurts
2021	—	`conf`	On the Transferability of Winning Tickets in Non-natural Image Datasets. VISIGRAPP (5: VISAPP) Matthia Sabatelli, Mike Kestemont, Pierre Geurts
2021	J	`jnl`	Optimizing model-agnostic Random Subspace ensembles. CoRR Vân Anh Huynh-Thu, Pierre Geurts
2021	—	`conf`	Sample-Free White-Box Out-of-Distribution Detection for Deep Learning. CVPR Workshops Jean-Michel Begon, Pierre Geurts
2021	—	`conf`	Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain. Computer Vision and Image Analysis of Art Nikolay Banar, Matthia Sabatelli, Pierre Geurts, Walter Daelemans, Mike Kestemont
2020	—	`ed.`	Artificial Intelligence and Machine Learning - 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium, November 6-8, 2019, Revised Selected Papers BNAIC/BENELEARN (Selected Papers) Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe
2020	J	`jnl`	Error curves for evaluating the quality of feature rankings. PeerJ Comput. Sci. Ivica Slavkov, Matej Petkovic, Pierre Geurts, Dragi Kocev, Saso Dzeroski
2020	J	`jnl`	Multi-task pre-training of deep neural networks for digital pathology. CoRR Romain Mormont, Pierre Geurts, Raphaël Marée
2020	B	`conf`	Nets Versus Trees for Feature Ranking and Gene Network Inference. DS Nicolas Vecoven, Jean-Michel Begon, Antonio Sutera, Pierre Geurts, Vân Anh Huynh-Thu
2020	J	`jnl`	On the Transferability of Winning Tickets in Non-Natural Image Datasets. CoRR Matthia Sabatelli, Mike Kestemont, Pierre Geurts
2020	J	`jnl`	QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning. CoRR Pascal Leroy, Damien Ernst, Pierre Geurts, Gilles Louppe, Jonathan Pisane, Matthia Sabatelli
2020	B	`conf`	The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms. IJCNN Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2019	J	`jnl`	Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms. CoRR Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2019	—	`conf`	Deep Quality-Value (DQV) Learning. BNAIC/BENELEARN Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2019	J	`jnl`	Gradient tree boosting with random output projections for multi-label classification and multi-output regression. CoRR Arnaud Joly, Louis Wehenkel, Pierre Geurts
2019	—	`ed.`	Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019. BNAIC/BENELEARN Katrien Beuls, Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, Paul Van Eecke
2018	—	`conf`	Comparison of Deep Transfer Learning Strategies for Digital Pathology. CVPR Workshops Romain Mormont, Pierre Geurts, Raphaël Marée
2018	J	`jnl`	Deep Quality-Value (DQV) Learning. CoRR Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2018	—	`conf`	Deep Transfer Learning for Art Classification Problems. ECCV Workshops (2) Matthia Sabatelli, Mike Kestemont, Walter Daelemans, Pierre Geurts
2018	J	`jnl`	Global multi-output decision trees for interaction prediction. Mach. Learn. Konstantinos Pliakos, Pierre Geurts, Celine Vens
2018	A	`conf`	Random Subspace with Trees for Feature Selection Under Memory Constraints. AISTATS Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
2017	B	`conf`	A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically. ACIVS Samir Azrour, Sébastien Piérard, Pierre Geurts, Marc Van Droogenbroeck
2017	—	`conf`	Automated Multimodal Volume Registration based on Supervised 3D Anatomical Landmark Detection. VISIGRAPP (5: VISAPP) Remy Vandaele, François Lallemand, Philippe Martinive, Akos Gulyban, Sébastien Jodogne, Philippe Coucke, Pierre Geurts, Raphaël Marée
2017	A*	`conf`	Globally Induced Forest: A Prepruning Compression Scheme. ICML Jean-Michel Begon, Arnaud Joly, Pierre Geurts
2017	J	`jnl`	Random Subspace with Trees for Feature Selection Under Memory Constraints. CoRR Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
2017	—	`conf`	Tree ensemble methods and parcelling to identify brain areas related to Alzheimer's disease. PRNI M. Wehenkel, Christine Bastin, Christophe Phillips, Pierre Geurts
2016	J	`jnl`	Collaborative analysis of multi-gigapixel imaging data using Cytomine. Bioinform. Raphaël Marée, Loic Rollus, Benjamin Stevens, Renaud Hoyoux, Gilles Louppe, Remy Vandaele, Jean-Michel Begon, Philipp Kainz, Pierre Geurts, Louis Wehenkel
2016	A	`conf`	Context-dependent feature analysis with random forests. UAI Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2016	J	`jnl`	Context-dependent feature analysis with random forests. CoRR Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2016	J	`jnl`	Towards generic image classification using tree-based learning: An extensive empirical study. Pattern Recognit. Lett. Raphaël Marée, Pierre Geurts, Louis Wehenkel
2015	J	`jnl`	Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge. IEEE Trans. Medical Imaging Ching-Wei Wang, Cheng-Ta Huang, Meng-Che Hsieh, Chung-Hsing Li, Sheng-Wei Chang, Wei-Cheng Li, Remy Vandaele, Raphaël Marée, Sébastien Jodogne, Pierre Geurts, Cheng Chen, Guoyan Zheng, Chengwen Chu, Hengameh Mirzaalian, Ghassan Hamarneh, Tomaz Vrtovec, Bulat Ibragimov
2015	J	`jnl`	Rating Network Paths for Locality-Aware Overlay Construction and Routing. IEEE/ACM Trans. Netw. Wei Du, Yongjun Liao, Narisu Tao, Pierre Geurts, Xiaoming Fu, Guy Leduc
2014	J	`jnl`	Classifying pairs with trees for supervised biological network inference. CoRR Marie Schrynemackers, Louis Wehenkel, M. Madan Babu, Pierre Geurts
2014	B	`conf`	Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis. ESANN Samir Azrour, Sébastien Piérard, Pierre Geurts, Marc Van Droogenbroeck
2014	—	`conf`	Random Forests with Random Projections of the Output Space for High Dimensional Multi-label Classification. ECML/PKDD (1) Arnaud Joly, Pierre Geurts, Louis Wehenkel
2014	J	`jnl`	Random forests with random projections of the output space for high dimensional multi-label classification. CoRR Arnaud Joly, Pierre Geurts, Louis Wehenkel
2014	—	`conf`	Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging. Neural Connectomics Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2014	J	`jnl`	Simple connectome inference from partial correlation statistics in calcium imaging. CoRR Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2013	J	`jnl`	DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction. IEEE/ACM Trans. Netw. Yongjun Liao, Wei Du, Pierre Geurts, Guy Leduc
2013	—	`conf`	Understanding variable importances in forests of randomized trees. NIPS Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts
2012	A	`conf`	Comparator selection for RPC with many labels. ECAI Samuel Hiard, Pierre Geurts, Louis Wehenkel
2012	J	`jnl`	DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction CoRR Yongjun Liao, Wei Du, Pierre Geurts, Guy Leduc
2012	—	`conf`	Embedding Monte Carlo Search of Features in Tree-Based Ensemble Methods. ECML/PKDD (1) Francis Maes, Pierre Geurts, Louis Wehenkel
2012	—	`conf`	Ensembles on Random Patches. ECML/PKDD (1) Gilles Louppe, Pierre Geurts
2012	B	`conf`	L1-based compression of random forest models. ESANN Arnaud Joly, François Schnitzler, Pierre Geurts, Louis Wehenkel
2012	J	`jnl`	Ordinal Rating of Network Performance and Inference by Matrix Completion CoRR Wei Du, Yongjun Liao, Pierre Geurts, Guy Leduc
2012	J	`jnl`	Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. Bioinform. Vân Anh Huynh-Thu, Yvan Saeys, Louis Wehenkel, Pierre Geurts
2011	—	`conf`	Automatic Localization of Interest Points in Zebrafish Images with Tree-Based Methods. PRIB Olivier Stern, Raphaël Marée, Jessica Aceto, Nathalie Jeanray, Marc Muller, Louis Wehenkel, Pierre Geurts
2011	A	`conf`	Decentralized prediction of end-to-end network performance classes. CoNEXT Yongjun Liao, Wei Du, Pierre Geurts, Guy Leduc
2011	—	`conf`	Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation. ECML/PKDD (3) François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel
2011	A	`conf`	Learning from positive and unlabeled examples by enforcing statistical significance. AISTATS Pierre Geurts
2011	—	`conf`	Learning to rank with extremely randomized trees. Yahoo! Learning to Rank Challenge Pierre Geurts, Gilles Louppe
2010	—	`ch.`	Bias vs Variance Decomposition for Regression and Classification. Data Mining and Knowledge Discovery Handbook Pierre Geurts
2010	—	`conf`	Biomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments. CLEF (Notebook Papers/LABs/Workshops) Raphaël Marée, Olivier Stern, Pierre Geurts
2010	J	`jnl`	Enhancement of TCP over wired/wireless networks with packet loss classifiers inferred by supervised learning. Wirel. Networks Ibtissam El Khayat, Pierre Geurts, Guy Leduc
2010	—	`conf`	Incremental indexing and distributed image search using shared randomized vocabularies. Multimedia Information Retrieval Raphaël Marée, Philippe Denis, Louis Wehenkel, Pierre Geurts
2010	B	`conf`	Network Distance Prediction Based on Decentralized Matrix Factorization. Networking Yongjun Liao, Pierre Geurts, Guy Leduc
2010	—	`conf`	Preface. MLSB Saso Dzeroski, Pierre Geurts, Juho Rousu
2010	—	`ed.`	Proceedings of the third International Workshop on Machine Learning in Systems Biology, MLSB 2009, Ljubljana, Slovenia, September 5-6, 2009 MLSB Saso Dzeroski, Pierre Geurts, Juho Rousu
2009	—	`conf`	A machine learning approach for material detection in hyperspectral images. CVPR Workshops Raphaël Marée, Benjamin Stevens, Pierre Geurts, Y. Guern, P. Mack
2009	J	`jnl`	Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees. IPSJ Trans. Comput. Vis. Appl. Raphaël Marée, Pierre Geurts, Louis Wehenkel
2009	B	`conf`	Detecting Triangle Inequality Violations in Internet Coordinate Systems by Supervised Learning. Networking Yongjun Liao, Mohamed Ali Kâafar, Bamba Gueye, François Cantin, Pierre Geurts, Guy Leduc
2009	—	`conf`	Fast Multi-class Image Annotation with Random Subwindows and Multiple Output Randomized Trees. VISAPP (2) Marie Dumont, Raphaël Marée, Louis Wehenkel, Pierre Geurts
2008	—	`conf`	Exploiting tree-based variable importances to selectively identify relevant variables. FSDM Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2007	—	`conf`	Content-Based Image Retrieval by Indexing Random Subwindows with Randomized Trees. ACCV (2) Raphaël Marée, Pierre Geurts, Louis Wehenkel
2007	J	`jnl`	Estimation of rotor angles of synchronous machines using artificial neural networks and local PMU-based quantities. Neurocomputing Alberto Del Angel, Pierre Geurts, Damien Ernst, Mevludin Glavic, Louis Wehenkel
2007	A*	`conf`	Gradient boosting for kernelized output spaces. ICML Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
2007	J	`jnl`	Inferring biological networks with output kernel trees. BMC Bioinform. Pierre Geurts, Nizar Touleimat, Marie Dutreix, Florence d'Alché-Buc
2007	J	`jnl`	Machine-learnt versus analytical models of TCP throughput. Comput. Networks Ibtissam El Khayat, Pierre Geurts, Guy Leduc
2006	—	`conf`	A Semi-Algebraic Description of Naive Bayes Models with Two Hidden Classes. AI&M Vincent Auvray, Pierre Geurts, Louis Wehenkel
2006	B	`conf`	Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data. ESANN Minh Quach, Pierre Geurts
2006	J	`jnl`	Extremely randomized trees. Mach. Learn. Pierre Geurts, Damien Ernst, Louis Wehenkel
2006	A*	`conf`	Kernelizing the output of tree-based methods. ICML Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
2006	B	`conf`	On the Accuracy of Analytical Models of TCP Throughput. Networking Ibtissam El Khayat, Pierre Geurts, Guy Leduc
2005	—	`ch.`	Bias vs. Variance Decomposition for Regression and Classification. The Data Mining and Knowledge Discovery Handbook Pierre Geurts
2005	—	`conf`	Biomedical Image Classification with Random Subwindows and Decision Trees. CVBIA Raphaël Marée, Pierre Geurts, Justus H. Piater, Louis Wehenkel
2005	A*	`conf`	Closed-form dual perturb and combine for tree-based models. ICML Pierre Geurts, Louis Wehenkel
2005	B	`conf`	Improving TCP in Wireless Networks with an Adaptive Machine-Learnt Classifier of Packet Loss Causes. NETWORKING Ibtissam El Khayat, Pierre Geurts, Guy Leduc
2005	J	`jnl`	Proteomic mass spectra classification using decision tree based ensemble methods. Bioinform. Pierre Geurts, Marianne Fillet, Dominique de Seny, Marie-Alice Meuwis, Michel Malaise, Marie-Paule Merville, Louis Wehenkel
2005	—	`conf`	Random Subwindows for Robust Image Classification. CVPR (1) Raphaël Marée, Pierre Geurts, Justus H. Piater, Louis Wehenkel
2005	C	`conf`	Segment and Combine Approach for Biological Sequence Classification. CIBCB Pierre Geurts, Antia Blanco Cuesta, Louis Wehenkel
2005	—	`conf`	Segment and Combine Approach for Non-parametric Time-Series Classification. PKDD Pierre Geurts, Louis Wehenkel
2005	J	`jnl`	Tree-Based Batch Mode Reinforcement Learning. J. Mach. Learn. Res. Damien Ernst, Pierre Geurts, Louis Wehenkel
2004	A*	`conf`	A Machine Learning Approach to Improve Congestion Control over Wireless Computer Networks. ICDM Pierre Geurts, Ibtissam El Khayat, Guy Leduc
2003	—	`conf`	A Comparison of Generic Machine Learning Algorithms for Image Classification. SGAI Conf. Raphaël Marée, Pierre Geurts, Giorgio Visimberga, Justus H. Piater, Louis Wehenkel
2003	—	`conf`	Iteratively Extending Time Horizon Reinforcement Learning. ECML Damien Ernst, Pierre Geurts, Louis Wehenkel
2002	—	`—`	Contributions to decision tree induction: bias/variance tradeoff and time series classification. Pierre Geurts
2001	A	`conf`	Dual perturb and combine algorithm. AISTATS Pierre Geurts
2001	—	`conf`	Pattern Extraction for Time Series Classification. PKDD Pierre Geurts
2000	—	`conf`	Investigation and Reduction of Discretization Variance in Decision Tree Induction. ECML Pierre Geurts, Louis Wehenkel
2000	—	`conf`	Some Enhencements of Decision Tree Bagging. PKDD Pierre Geurts
2000	—	`conf`	Temporal Machine Learning for Switching Control. PKDD Pierre Geurts, Louis Wehenkel