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ORCIDYves Grandvalet
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- affiliation: University of Technology of Compiègne, France
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2020 – today
- 2024
[c39]Nicolas Urbani
, Sylvain Rousseau, Yves Grandvalet, Leonardo Tanzi:
Harnessing Superclasses for Learning from Hierarchical Databases. ECML/PKDD (4) 2024: 247-265- [i8]Nicolas Urbani, Sylvain Rousseau, Yves Grandvalet, Leonardo Tanzi:
Harnessing Superclasses for Learning from Hierarchical Databases. CoRR abs/2411.16438 (2024) - 2023
- [i7]Philippe Carvalho, Alexandre Durupt, Yves Grandvalet:
A Review of Benchmarks for Visual Defect Detection in the Manufacturing Industry. CoRR abs/2305.13261 (2023) - 2022
- [j21]Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet:
Learning from missing data with the binary latent block model. Stat. Comput. 32(1): 9 (2022) - 2021
- [c38]Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet:
Stereotype-aware collaborative filtering. FedCSIS 2021: 69-79 - [c37]Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet:
Co-clustering for Fair Recommendation. PKDD/ECML Workshops (1) 2021: 607-630 - [c36]Abdelhak Loukkal, Yves Grandvalet, Tom Drummond, You Li:
Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning. WACV 2021: 51-60 - 2020
- [j20]Xuhong Li, Yves Grandvalet, Franck Davoine, Jingchun Cheng, Yin Cui, Han Zhang, Serge J. Belongie, Yi-Hsuan Tsai, Ming-Hsuan Yang:
Transfer learning in computer vision tasks: Remember where you come from. Image Vis. Comput. 93: 103853 (2020) - [j19]Xuhong Li, Yves Grandvalet, Franck Davoine:
A baseline regularization scheme for transfer learning with convolutional neural networks. Pattern Recognit. 98 (2020) - [i6]Xuhong Li, Yves Grandvalet, Rémi Flamary, Nicolas Courty, Dejing Dou:
Representation Transfer by Optimal Transport. CoRR abs/2007.06737 (2020) - [i5]Abdelhak Loukkal, Yves Grandvalet, Tom Drummond, You Li:
Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning. CoRR abs/2008.04047 (2020) - [i4]Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet:
Learning from missing data with the Latent Block Model. CoRR abs/2010.12222 (2020)
2010 – 2019
- 2019
- [c35]Abdelhak Loukkal, Yves Grandvalet, You Li:
Disparity weighted loss for semantic segmentation of driving scenes. ITSC 2019: 3427-3432 - 2018
- [j18]Aurore Lomet, Gérard Govaert, Yves Grandvalet:
Model selection for Gaussian latent block clustering with the integrated classification likelihood. Adv. Data Anal. Classif. 12(3): 489-508 (2018) - [c34]Abdelhak Loukkal, Vincent Frémont, Yves Grandvalet, You Li:
Improving semantic segmentation in urban scenes with a cartographic information. ICARCV 2018: 400-406 - [c33]Xuhong Li, Yves Grandvalet, Franck Davoine:
Explicit Inductive Bias for Transfer Learning with Convolutional Networks. ICML 2018: 2830-2839 - [c32]Xuhong Li, Franck Davoine, Yves Grandvalet:
A Simple Weight Recall for Semantic Segmentation: Application to Urban Scenes. Intelligent Vehicles Symposium 2018: 1007-1012 - [i3]Xuhong Li, Yves Grandvalet, Franck Davoine:
Explicit Inductive Bias for Transfer Learning with Convolutional Networks. CoRR abs/1802.01483 (2018) - 2017
- [j17]Jean-Michel Bécu, Yves Grandvalet, Christophe Ambroise, Cyril Dalmasso:
Beyond support in two-stage variable selection. Stat. Comput. 27(1): 169-179 (2017) - 2016
- [j16]Alberto García-Durán, Antoine Bordes, Nicolas Usunier, Yves Grandvalet:
Combining Two and Three-Way Embedding Models for Link Prediction in Knowledge Bases. J. Artif. Intell. Res. 55: 715-742 (2016) - [c31]Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet:
A Coverage-Based Approach to Recommendation Diversity On Similarity Graph. RecSys 2016: 15-22 - 2015
- [j15]Marta Avalos, Hélène Pouyes, Yves Grandvalet, Ludivine Orriols, Emmanuel Lagarde:
Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm. BMC Bioinform. 16(S-6): S1 (2015) - [j14]Xiao Liu, Antoine Bordes, Yves Grandvalet:
Extracting biomedical events from pairs of text entities. BMC Bioinform. 16(S10): S8 (2015) - [c30]Jean-Michel Bécu, Christophe Ambroise, Yves Grandvalet, Cyril Dalmasso:
Significance testing for variable selection in high-dimension. CIBCB 2015: 1-8 - [i2]Shameem Ahamed Puthiya Parambath, Nicolas Usunier, Yves Grandvalet:
Theory of Optimizing Pseudolinear Performance Measures: Application to F-measure. CoRR abs/1505.00199 (2015) - [i1]Alberto García-Durán, Antoine Bordes, Nicolas Usunier, Yves Grandvalet:
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases. CoRR abs/1506.00999 (2015) - 2014
- [c29]Xiao Liu, Antoine Bordes, Yves Grandvalet:
Fast Recursive Multi-class Classification of Pairs of Text Entities for Biomedical Event Extraction. EACL 2014: 692-701 - [c28]Marie Szafranski, Yves Grandvalet:
KEOPS: Kernels organized into pyramids. ICASSP 2014: 8262-8266 - [c27]Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet:
Optimizing F-Measures by Cost-Sensitive Classification. NIPS 2014: 2123-2131 - 2013
- [c26]Xiao Liu, Antoine Bordes, Yves Grandvalet:
Biomedical Event Extraction by Multi-class Classification of Pairs of Text Entities. BioNLP@ACL (Shared Task) 2013: 45-49 - [c25]Marta Avalos, Yves Grandvalet, Hélène Pouyes, Ludivine Orriols, Emmanuel Lagarde:
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. CIBB 2013: 109-124 - 2012
- [c24]Aurore Lomet, Gérard Govaert, Yves Grandvalet:
An Approximation of the Integrated Classification Likelihood for the Latent Block Model. ICDM Workshops 2012: 147-153 - [c23]Luis Francisco Sánchez Merchante, Yves Grandvalet, Gérard Govaert:
An Efficient Approach to Sparse Linear Discriminant Analysis. ICML 2012 - 2011
- [j13]Julien Chiquet, Yves Grandvalet, Christophe Ambroise:
Inferring multiple graphical structures. Stat. Comput. 21(4): 537-553 (2011) - 2010
- [j12]Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning. Mach. Learn. 79(1-2): 73-103 (2010)
2000 – 2009
- 2009
- [j11]Jean-François Paiement, Yves Grandvalet, Samy Bengio:
Predictive models for music. Connect. Sci. 21(2&3): 253-272 (2009) - 2008
- [c22]Jean-François Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck:
A distance model for rhythms. ICML 2008: 736-743 - [c21]Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning. ICML 2008: 1040-1047 - [c20]Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu:
Support Vector Machines with a Reject Option. NIPS 2008: 537-544 - 2007
- [j10]Marta Avalos, Yves Grandvalet, Christophe Ambroise:
Parsimonious additive models. Comput. Stat. Data Anal. 51(6): 2851-2870 (2007) - [c19]Romain Hérault, Yves Grandvalet:
Sparse probabilistic classifiers. ICML 2007: 337-344 - [c18]Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet:
More efficiency in multiple kernel learning. ICML 2007: 775-782 - [c17]Marie Szafranski, Yves Grandvalet, Pierre Morizet-Mahoudeaux:
Hierarchical Penalization. NIPS 2007: 1457-1464 - 2006
- [c16]Romain Hérault, Franck Davoine, Yves Grandvalet:
Head and Facial Action Tracking: Comparison of Two Robust Approaches. FGR 2006: 287-292 - [p1]Yves Grandvalet, Yoshua Bengio:
Entropy Regularization. Semi-Supervised Learning 2006: 151-168 - 2005
- [j9]Marta Avalos, Yves Grandvalet, Christophe Ambroise:
Discrimination par modèles additifs parcimonieux. Rev. d'Intelligence Artif. 19(4-5): 661-682 (2005) - [c15]Yves Grandvalet, Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization. CAP 2005: 281-296 - [c14]Yves Grandvalet, Johnny Mariéthoz, Samy Bengio:
A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification. NIPS 2005: 467-474 - 2004
- [j8]Yoshua Bengio, Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation. J. Mach. Learn. Res. 5: 1089-1105 (2004) - [j7]Yves Grandvalet:
Bagging Equalizes Influence. Mach. Learn. 55(3): 251-270 (2004) - [c13]Yves Grandvalet, Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization. NIPS 2004: 529-536 - [c12]Sandro Glaucio Maquiné de Souza, Thierry Denoeux, Yves Grandvalet:
Recycling experiments for sludge monitoring in waste water treatment. SMC (2) 2004: 1342-1347 - 2003
- [j6]Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger:
Resample and combine: an approach to improving uncertainty representation in evidential pattern classification. Inf. Fusion 4(2): 75-85 (2003) - [j5]Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger:
Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification. Inf. Fusion 4(3): 235-236 (2003) - [c11]Marta Avalos, Yves Grandvalet, Christophe Ambroise:
Regularization Methods for Additive Models. IDA 2003: 509-520 - [c10]Yoshua Bengio, Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation. NIPS 2003: 513-520 - 2002
- [c9]Yves Grandvalet, Stéphane Canu:
Adaptive Scaling for Feature Selection in SVMs. NIPS 2002: 553-560 - 2001
- [j4]Yves Grandvalet:
Injection de bruit adaptative pour la détermination de variables pertinentes. Rev. d'Intelligence Artif. 15(3-4): 351-371 (2001) - [c8]Yves Grandvalet, Florence d'Alché-Buc, Christophe Ambroise:
Boosting Mixture Models for Semi-supervised Learning. ICANN 2001: 41-48 - [c7]Yves Grandvalet:
Bagging Can Stabilize without Reducing Variance. ICANN 2001: 49-56 - [c6]Florence d'Alché-Buc, Yves Grandvalet, Christophe Ambroise:
Semi-supervised MarginBoost. NIPS 2001: 553-560 - 2000
- [j3]Yves Grandvalet:
Anisotropic noise injection for input variables relevance determination. IEEE Trans. Neural Networks Learn. Syst. 11(6): 1201-1212 (2000) - [c5]Yves Grandvalet:
Bagging Down-Weights Leverage Points. IJCNN (4) 2000: 505-510
1990 – 1999
- 1998
- [c4]Yves Grandvalet, Stéphane Canu:
Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage. NIPS 1998: 445-451 - 1997
- [j2]Yves Grandvalet, Stéphane Canu, Stéphane Boucheron:
Noise Injection: Theoretical Prospects. Neural Comput. 9(5): 1093-1108 (1997) - [c3]Skander Soltani, Stéphane Canu, Daniel Boichu, Yves Grandvalet:
Wavelet Frames Based Estimator. ICANN 1997: 319-324 - [c2]Yves Grandvalet, Stéphane Canu:
Adaptive Noise Injection for Input Variables Relevance Determination. ICANN 1997: 463-468 - 1995
- [j1]Yves Grandvalet, Stéphane Canu:
Comments on "Noise injection into inputs in back propagation learning". IEEE Trans. Syst. Man Cybern. 25(4): 678-681 (1995) - [c1]Yves Grandvalet, Stéphane Canu, Stéphane Boucheron:
Control of complexity in learning with perturbed inputs. ESANN 1995
Coauthor Index
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