Geurts, Pierre

30 publications

MLJ 2025 Hybrid Additive Modeling with Partial Dependence for Supervised Regression and Dynamical Systems Forecasting Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts

MLJ 2024 Optimizing Model-Agnostic Random Subspace Ensembles Vân Anh Huynh-Thu, Pierre Geurts

ICMLW 2023 Knowledge-Guided Additive Modeling for Supervised Regression Yann Claes, Van Anh Huynh-Thu, Pierre Geurts

ECCVW 2022 Empirical Evaluation of Deep Learning Approaches for Landmark Detection in Fish Bioimages Navdeep Kumar, Claudia Di Biagio, Zachary Dellacqua, Ratish Raman, Arianna Martini, Clara Boglione, Marc Muller, Pierre Geurts, Raphaël Marée

ECCVW 2022 Relieving Pixel-Wise Labeling Effort for Pathology Image Segmentation with Self-Training Romain Mormont, Mehdi Testouri, Raphaël Marée, Pierre Geurts

NeurIPS 2021 From Global to Local MDI Variable Importances for Random Forests and When They Are Shapley Values Antonio Sutera, Gilles Louppe, Van Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts

NeurIPSW 2021 On the Transferability of Deep-Q Networks Matthia Sabatelli, Pierre Geurts

CVPRW 2021 Sample-Free White-Box Out-of-Distribution Detection for Deep Learning Jean-Michel Begon, Pierre Geurts

CVPRW 2018 Comparison of Deep Transfer Learning Strategies for Digital Pathology Romain Mormont, Pierre Geurts, Raphaël Marée

ECCVW 2018 Deep Transfer Learning for Art Classification Problems Matthia Sabatelli, Mike Kestemont, Walter Daelemans, Pierre Geurts

MLJ 2018 Global Multi-Output Decision Trees for Interaction Prediction Konstantinos Pliakos, Pierre Geurts, Celine Vens

AISTATS 2018 Random Subspace with Trees for Feature Selection Under Memory Constraints Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts

ICML 2017 Globally Induced Forest: A Prepruning Compression Scheme Jean-Michel Begon, Arnaud Joly, Pierre Geurts

UAI 2016 Context-Dependent Feature Analysis with Random Forests Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts

ECML-PKDD 2014 Random Forests with Random Projections of the Output Space for High Dimensional Multi-Label Classification Arnaud Joly, Pierre Geurts, Louis Wehenkel

NeurIPS 2013 Understanding Variable Importances in Forests of Randomized Trees Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts

ECML-PKDD 2012 Embedding Monte Carlo Search of Features in Tree-Based Ensemble Methods Francis Maes, Pierre Geurts, Louis Wehenkel

ECML-PKDD 2012 Ensembles on Random Patches Gilles Louppe, Pierre Geurts

ECML-PKDD 2011 Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel

AISTATS 2011 Learning from Positive and Unlabeled Examples by Enforcing Statistical Significance Pierre Geurts

CVPRW 2009 A Machine Learning Approach for Material Detection in Hyperspectral Images Raphaël Marée, Benjamin Stevens, Pierre Geurts, Y. Guern, P. Mack

ICML 2007 Gradient Boosting for Kernelized Output Spaces Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc

MLJ 2006 Extremely Randomized Trees Pierre Geurts, Damien Ernst, Louis Wehenkel

ICML 2006 Kernelizing the Output of Tree-Based Methods Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc

ICML 2005 Closed-Form Dual Perturb and Combine for Tree-Based Models Pierre Geurts, Louis Wehenkel

CVPR 2005 Random Subwindows for Robust Image Classification Raphaël Marée, Pierre Geurts, Justus H. Piater, Louis Wehenkel

JMLR 2005 Tree-Based Batch Mode Reinforcement Learning Damien Ernst, Pierre Geurts, Louis Wehenkel

ECML-PKDD 2003 Iteratively Extending Time Horizon Reinforcement Learning Damien Ernst, Pierre Geurts, Louis Wehenkel

AISTATS 2001 Dual Perturb and Combine Algorithm Pierre Geurts

ECML-PKDD 2000 Investigation and Reduction of Discretization Variance in Decision Tree Induction Pierre Geurts, Louis Wehenkel