Control of complexity in learning with perturbed inputs. - Yves Grandvalet; Stéphane Canu; Stéphane Boucheron (ESANN, 1995)

Comments on "Noise injection into inputs in back propagation learning". - Yves Grandvalet; Stéphane Canu (IEEE Trans. Syst. Man Cybern., 1995)

Adaptive Noise Injection for Input Variables Relevance Determination. - Yves Grandvalet; Stéphane Canu (ICANN, 1997)

Wavelet Frames Based Estimator. - Skander Soltani; Stéphane Canu; Daniel Boichu; Yves Grandvalet (ICANN, 1997)

Noise Injection: Theoretical Prospects. - Yves Grandvalet; Stéphane Canu; Stéphane Boucheron (Neural Comput., 1997)

Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage. - Yves Grandvalet; Stéphane Canu (NIPS, 1998)

Bagging Down-Weights Leverage Points. - Yves Grandvalet (IJCNN (4), 2000)

Anisotropic noise injection for input variables relevance determination. - Yves Grandvalet (IEEE Trans. Neural Networks Learn. Syst., 2000)

Bagging Can Stabilize without Reducing Variance. - Yves Grandvalet (ICANN, 2001)

Boosting Mixture Models for Semi-supervised Learning. - Yves Grandvalet; Florence d'Alché-Buc; Christophe Ambroise (ICANN, 2001)

Semi-supervised MarginBoost. - Florence d'Alché-Buc; Yves Grandvalet; Christophe Ambroise (NIPS, 2001)

Injection de bruit adaptative pour la détermination de variables pertinentes. - Yves Grandvalet (Rev. d'Intelligence Artif., 2001)

Adaptive Scaling for Feature Selection in SVMs. - Yves Grandvalet; Stéphane Canu (NIPS, 2002)

Regularization Methods for Additive Models. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (IDA, 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)

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)

Semi-supervised Learning by Entropy Minimization. - Yves Grandvalet; Yoshua Bengio (NIPS, 2004)

Recycling experiments for sludge monitoring in waste water treatment. - Sandro Glaucio Maquiné de Souza; Thierry Denoeux; Yves Grandvalet (SMC (2), 2004)

No Unbiased Estimator of the Variance of K-Fold Cross-Validation. - Yoshua Bengio; Yves Grandvalet (J. Mach. Learn. Res., 2004)

Bagging Equalizes Influence. - Yves Grandvalet (Mach. Learn., 2004)

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification. - Yves Grandvalet; Johnny Mariéthoz; Samy Bengio (NIPS, 2005)

Discrimination par modèles additifs parcimonieux. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (Rev. d'Intelligence Artif., 2005)

Entropy Regularization. - Yves Grandvalet; Yoshua Bengio (Semi-Supervised Learning, 2006)

Head and Facial Action Tracking: Comparison of Two Robust Approaches. - Romain Hérault; Franck Davoine; Yves Grandvalet (FGR, 2006)

Sparse probabilistic classifiers. - Romain Hérault; Yves Grandvalet (ICML, 2007)

More efficiency in multiple kernel learning. - Alain Rakotomamonjy; Francis R. Bach; Stéphane Canu; Yves Grandvalet (ICML, 2007)

Hierarchical Penalization. - Marie Szafranski; Yves Grandvalet; Pierre Morizet-Mahoudeaux (NIPS, 2007)

Parsimonious additive models. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (Comput. Stat. Data Anal., 2007)

A distance model for rhythms. - Jean-François Paiement; Yves Grandvalet; Samy Bengio; Douglas Eck (ICML, 2008)

Support Vector Machines with a Reject Option. - Yves Grandvalet; Alain Rakotomamonjy; Joseph Keshet; Stéphane Canu (NIPS, 2008)

Predictive models for music. - Jean-François Paiement; Yves Grandvalet; Samy Bengio (Connect. Sci., 2009)

Composite kernel learning. - Marie Szafranski; Yves Grandvalet; Alain Rakotomamonjy (Mach. Learn., 2010)

Inferring multiple graphical structures. - Julien Chiquet; Yves Grandvalet; Christophe Ambroise (Stat. Comput., 2011)

An Approximation of the Integrated Classification Likelihood for the Latent Block Model. - Aurore Lomet; Gérard Govaert; Yves Grandvalet (ICDM Workshops, 2012)

An Efficient Approach to Sparse Linear Discriminant Analysis. - Luis Francisco Sánchez Merchante; Yves Grandvalet; Gérard Govaert (ICML, 2012)

Biomedical Event Extraction by Multi-class Classification of Pairs of Text Entities. - Xiao Liu 009; Antoine Bordes; Yves Grandvalet (BioNLP@ACL (Shared Task), 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 (CIBB, 2013)

Fast Recursive Multi-class Classification of Pairs of Text Entities for Biomedical Event Extraction. - Xiao Liu 009; Antoine Bordes; Yves Grandvalet (EACL, 2014)

KEOPS: Kernels organized into pyramids. - Marie Szafranski; Yves Grandvalet (ICASSP, 2014)

Optimizing F-Measures by Cost-Sensitive Classification. - Shameem Puthiya Parambath; Nicolas Usunier; Yves Grandvalet (NIPS, 2014)

Significance testing for variable selection in high-dimension. - Jean-Michel Bécu; Christophe Ambroise; Yves Grandvalet; Cyril Dalmasso (CIBCB, 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)

Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases. - Alberto García-Durán; Antoine Bordes; Nicolas Usunier; Yves Grandvalet (CoRR, 2015)

Theory of Optimizing Pseudolinear Performance Measures: Application to F-measure. - Shameem Ahamed Puthiya Parambath; Nicolas Usunier; Yves Grandvalet (CoRR, 2015)

Extracting biomedical events from pairs of text entities. - Xiao Liu 009; Antoine Bordes; Yves Grandvalet (BMC Bioinform., 2015)

A Coverage-Based Approach to Recommendation Diversity On Similarity Graph. - Shameem Puthiya Parambath; Nicolas Usunier; Yves Grandvalet (RecSys, 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)

Beyond support in two-stage variable selection. - Jean-Michel Bécu; Yves Grandvalet; Christophe Ambroise; Cyril Dalmasso (Stat. Comput., 2017)

Improving semantic segmentation in urban scenes with a cartographic information. - Abdelhak Loukkal; Vincent Frémont; Yves Grandvalet; You Li 005 (ICARCV, 2018)

Explicit Inductive Bias for Transfer Learning with Convolutional Networks. - Xuhong Li 002; Yves Grandvalet; Franck Davoine (ICML, 2018)

A Simple Weight Recall for Semantic Segmentation: Application to Urban Scenes. - Xuhong Li 002; Franck Davoine; Yves Grandvalet (Intelligent Vehicles Symposium, 2018)

Model selection for Gaussian latent block clustering with the integrated classification likelihood. - Aurore Lomet; Gérard Govaert; Yves Grandvalet (Adv. Data Anal. Classif., 2018)

Disparity weighted loss for semantic segmentation of driving scenes. - Abdelhak Loukkal; Yves Grandvalet; You Li 005 (ITSC, 2019)

Representation Transfer by Optimal Transport. - Xuhong Li 002; Yves Grandvalet; Rémi Flamary; Nicolas Courty; Dejing Dou (CoRR, 2020)

Learning from missing data with the Latent Block Model. - Gabriel Frisch; Jean-Benoist Léger; Yves Grandvalet (CoRR, 2020)

Transfer learning in computer vision tasks: Remember where you come from. - Xuhong Li 002; Yves Grandvalet; Franck Davoine; Jingchun Cheng; Yin Cui; Han Zhang 005; Serge J. Belongie; Yi-Hsuan Tsai; Ming-Hsuan Yang 001 (Image Vis. Comput., 2020)

A baseline regularization scheme for transfer learning with convolutional neural networks. - Xuhong Li 002; Yves Grandvalet; Franck Davoine (Pattern Recognit., 2020)

Stereotype-aware collaborative filtering. - Gabriel Frisch; Jean-Benoist Léger; Yves Grandvalet (FedCSIS, 2021)

Co-clustering for Fair Recommendation. - Gabriel Frisch; Jean-Benoist Léger; Yves Grandvalet (PKDD/ECML Workshops (1), 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 005 (WACV, 2021)

Learning from missing data with the binary latent block model. - Gabriel Frisch; Jean-Benoist Léger; Yves Grandvalet (Stat. Comput., 2022)

A Review of Benchmarks for Visual Defect Detection in the Manufacturing Industry. - Philippe Carvalho; Alexandre Durupt; Yves Grandvalet (CoRR, 2023)

Harnessing Superclasses for Learning from Hierarchical Databases. - Nicolas Urbani; Sylvain Rousseau 001; Yves Grandvalet; Leonardo Tanzi (ECML/PKDD (4), 2024)