Yves Grandvalet

According to our database, Yves Grandvalet authored at least 63 papers between 1995 and 2024.

Collaborative distances:

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

2024

Harnessing Superclasses for Learning from Hierarchical Databases.

Nicolas Urbani, Sylvain Rousseau, Yves Grandvalet, Leonardo Tanzi

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

2023

A Review of Benchmarks for Visual Defect Detection in the Manufacturing Industry.

Philippe Carvalho, Alexandre Durupt, Yves Grandvalet

CoRR, 2023

2022

Learning from missing data with the binary latent block model.

Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet

Stat. Comput., 2022

2021

Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning.

Abdelhak Loukkal, Yves Grandvalet, Tom Drummond, You Li

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Co-clustering for Fair Recommendation.

Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Stereotype-aware collaborative filtering.

Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet

Proceedings of the 16th Conference on Computer Science and Intelligence Systems, 2021

2020

A baseline regularization scheme for transfer learning with convolutional neural networks.

Xuhong Li, Yves Grandvalet, Franck Davoine

Pattern Recognit., 2020

Transfer learning in computer vision tasks: Remember where you come from.

Xuhong Li, Yves Grandvalet, Franck Davoine, Jingchun Cheng, Yin Cui, Han Zhang, Serge J. Belongie, Yi-Hsuan Tsai, Ming-Hsuan Yang

Image Vis. Comput., 2020

Learning from missing data with the Latent Block Model.

Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet

CoRR, 2020

Representation Transfer by Optimal Transport.

Xuhong Li, Yves Grandvalet, Rémi Flamary, Nicolas Courty, Dejing Dou

CoRR, 2020

2019

Disparity weighted loss for semantic segmentation of driving scenes.

Abdelhak Loukkal, Yves Grandvalet, You Li

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

2018

Model selection for Gaussian latent block clustering with the integrated classification likelihood.

Aurore Lomet, Gérard Govaert, Yves Grandvalet

Adv. Data Anal. Classif., 2018

A Simple Weight Recall for Semantic Segmentation: Application to Urban Scenes.

Xuhong Li, Franck Davoine, Yves Grandvalet

Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

Explicit Inductive Bias for Transfer Learning with Convolutional Networks.

Xuhong Li, Yves Grandvalet, Franck Davoine

Proceedings of the 35th International Conference on Machine Learning, 2018

Improving semantic segmentation in urban scenes with a cartographic information.

Abdelhak Loukkal, Vincent Frémont, Yves Grandvalet, You Li

Proceedings of the 15th International Conference on Control, 2018

2017

Beyond support in two-stage variable selection.

Jean-Michel Bécu, Yves Grandvalet, Christophe Ambroise, Cyril Dalmasso

Stat. Comput., 2017

2016

Combining Two and Three-Way Embedding Models for Link Prediction in Knowledge Bases.

Alberto García-Durán, Antoine Bordes, Nicolas Usunier, Yves Grandvalet

J. Artif. Intell. Res., 2016

A Coverage-Based Approach to Recommendation Diversity On Similarity Graph.

Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015

Extracting biomedical events from pairs of text entities.

Xiao Liu, Antoine Bordes, Yves Grandvalet

BMC Bioinform., December, 2015

Theory of Optimizing Pseudolinear Performance Measures: Application to F-measure.

Shameem Ahamed Puthiya Parambath, Nicolas Usunier, Yves Grandvalet

CoRR, 2015

Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases.

Alberto García-Durán, Antoine Bordes, Nicolas Usunier, Yves Grandvalet

CoRR, 2015

Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm.

Marta Avalos, Hélène Pouyes, Yves Grandvalet, Ludivine Orriols, Emmanuel Lagarde

BMC Bioinform., 2015

Significance testing for variable selection in high-dimension.

Jean-Michel Bécu, Christophe Ambroise, Yves Grandvalet, Cyril Dalmasso

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2015

2014

Optimizing F-Measures by Cost-Sensitive Classification.

Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

KEOPS: Kernels organized into pyramids.

Marie Szafranski, Yves Grandvalet

Proceedings of the IEEE International Conference on Acoustics, 2014

Fast Recursive Multi-class Classification of Pairs of Text Entities for Biomedical Event Extraction.

Xiao Liu, Antoine Bordes, Yves Grandvalet

Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014

2013

High-Dimensional Sparse Matched Case-Control and Case-Crossover Data: A Review of Recent Works, Description of an R Tool and an Illustration of the Use in Epidemiological Studies.

Marta Avalos, Yves Grandvalet, Hélène Pouyes, Ludivine Orriols, Emmanuel Lagarde

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2013

Biomedical Event Extraction by Multi-class Classification of Pairs of Text Entities.

Xiao Liu, Antoine Bordes, Yves Grandvalet

Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, 2013

2012

An Efficient Approach to Sparse Linear Discriminant Analysis.

Luis Francisco Sánchez Merchante, Yves Grandvalet, Gérard Govaert

Proceedings of the 29th International Conference on Machine Learning, 2012

An Approximation of the Integrated Classification Likelihood for the Latent Block Model.

Aurore Lomet, Gérard Govaert, Yves Grandvalet

Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

2011

Inferring multiple graphical structures.

Julien Chiquet, Yves Grandvalet, Christophe Ambroise

Stat. Comput., 2011

2010

Composite kernel learning.

Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy

Mach. Learn., 2010

2009

Predictive models for music.

Jean-François Paiement, Yves Grandvalet, Samy Bengio

Connect. Sci., 2009

2008

Support Vector Machines with a Reject Option.

Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

A distance model for rhythms.

Jean-François Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck

Proceedings of the Machine Learning, 2008

2007

Parsimonious additive models.

Marta Avalos, Yves Grandvalet, Christophe Ambroise

Comput. Stat. Data Anal., 2007

Hierarchical Penalization.

Marie Szafranski, Yves Grandvalet, Pierre Morizet-Mahoudeaux

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

More efficiency in multiple kernel learning.

Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet

Proceedings of the Machine Learning, 2007

Sparse probabilistic classifiers.

Romain Hérault, Yves Grandvalet

Proceedings of the Machine Learning, 2007

2006

Head and Facial Action Tracking: Comparison of Two Robust Approaches.

Romain Hérault, Franck Davoine, Yves Grandvalet

Proceedings of the Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FGR 2006), 2006

Entropy Regularization.

Yves Grandvalet, Yoshua Bengio

Proceedings of the Semi-Supervised Learning, 2006

2005

Discrimination par modèles additifs parcimonieux.

Marta Avalos, Yves Grandvalet, Christophe Ambroise

Rev. d'Intelligence Artif., 2005

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification.

Yves Grandvalet, Johnny Mariéthoz, Samy Bengio

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004

Bagging Equalizes Influence.

Yves Grandvalet

Mach. Learn., 2004

No Unbiased Estimator of the Variance of K-Fold Cross-Validation.

Yoshua Bengio, Yves Grandvalet

J. Mach. Learn. Res., 2004

Recycling experiments for sludge monitoring in waste water treatment.

Sandro Glaucio Maquiné de Souza, Thierry Denoeux, Yves Grandvalet

Proceedings of the IEEE International Conference on Systems, 2004

Semi-supervised Learning by Entropy Minimization.

Yves Grandvalet, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003

Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification.

Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger

Inf. Fusion, 2003

Resample and combine: an approach to improving uncertainty representation in evidential pattern classification.

Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger

Inf. Fusion, 2003

Regularization Methods for Additive Models.

Marta Avalos, Yves Grandvalet, Christophe Ambroise

Proceedings of the Advances in Intelligent Data Analysis V, 2003

2002

Adaptive Scaling for Feature Selection in SVMs.

Yves Grandvalet, Stéphane Canu

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Injection de bruit adaptative pour la détermination de variables pertinentes.

Yves Grandvalet

Rev. d'Intelligence Artif., 2001

Semi-supervised MarginBoost.

Florence d'Alché-Buc, Yves Grandvalet, Christophe Ambroise

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Boosting Mixture Models for Semi-supervised Learning.

Yves Grandvalet, Florence d'Alché-Buc, Christophe Ambroise

Proceedings of the Artificial Neural Networks, 2001

Bagging Can Stabilize without Reducing Variance.

Yves Grandvalet

Proceedings of the Artificial Neural Networks, 2001

2000

Anisotropic noise injection for input variables relevance determination.

Yves Grandvalet

IEEE Trans. Neural Networks Learn. Syst., 2000

Bagging Down-Weights Leverage Points.

Yves Grandvalet

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1998

Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage.

Yves Grandvalet, Stéphane Canu

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997

Noise Injection: Theoretical Prospects.

Yves Grandvalet, Stéphane Canu, Stéphane Boucheron

Neural Comput., 1997

Wavelet Frames Based Estimator.

Skander Soltani, Stéphane Canu, Daniel Boichu, Yves Grandvalet

Proceedings of the Artificial Neural Networks, 1997

Adaptive Noise Injection for Input Variables Relevance Determination.

Yves Grandvalet, Stéphane Canu

Proceedings of the Artificial Neural Networks, 1997

1995

Comments on "Noise injection into inputs in back propagation learning".

Yves Grandvalet, Stéphane Canu

IEEE Trans. Syst. Man Cybern., 1995

Control of complexity in learning with perturbed inputs.

Yves Grandvalet, Stéphane Canu, Stéphane Boucheron

Proceedings of the 3rd European Symposium on Artificial Neural Networks, 1995