| 2008 |
|---|
| 28 | EE | Marie Szafranski,
Yves Grandvalet,
Alain Rakotomamonjy:
Composite kernel learning.
ICML 2008: 1040-1047 |
| 27 | EE | Jean-François Paiement,
Yves Grandvalet,
Samy Bengio,
Douglas Eck:
A distance model for rhythms.
ICML 2008: 736-743 |
| 26 | EE | Yves Grandvalet,
Alain Rakotomamonjy,
Joseph Keshet,
Stéphane Canu:
Support Vector Machines with a Reject Option.
NIPS 2008: 537-544 |
| 2007 |
|---|
| 25 | EE | Romain Hérault,
Yves Grandvalet:
Sparse probabilistic classifiers.
ICML 2007: 337-344 |
| 24 | EE | Alain Rakotomamonjy,
Francis Bach,
Stéphane Canu,
Yves Grandvalet:
More efficiency in multiple kernel learning.
ICML 2007: 775-782 |
| 23 | EE | Marie Szafranski,
Yves Grandvalet,
Pierre Morizet-Mahoudeaux:
Hierarchical Penalization.
NIPS 2007 |
| 22 | EE | Marta Avalos,
Yves Grandvalet,
Christophe Ambroise:
Parsimonious additive models.
Computational Statistics & Data Analysis 51(6): 2851-2870 (2007) |
| 2006 |
|---|
| 21 | EE | Romain Hérault,
Franck Davoine,
Yves Grandvalet:
Head and Facial Action Tracking: Comparison of Two Robust Approaches.
FG 2006: 287-292 |
| 2005 |
|---|
| 20 | | Yves Grandvalet,
Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization.
CAP 2005: 281-296 |
| 19 | EE | Yves Grandvalet,
Johnny Mariéthoz,
Samy Bengio:
A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification.
NIPS 2005 |
| 18 | EE | Marta Avalos,
Yves Grandvalet,
Christophe Ambroise:
Discrimination par modèles additifs parcimonieux.
Revue d'Intelligence Artificielle 19(4-5): 661-682 (2005) |
| 2004 |
|---|
| 17 | EE | Yves Grandvalet,
Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization.
NIPS 2004 |
| 16 | EE | Sandro Glaucio Maquiné de Souza,
Thierry Denoeux,
Yves Grandvalet:
Recycling experiments for sludge monitoring in waste water treatment.
SMC (2) 2004: 1342-1347 |
| 15 | EE | Yoshua Bengio,
Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation.
Journal of Machine Learning Research 5: 1089-1105 (2004) |
| 14 | EE | Yves Grandvalet:
Bagging Equalizes Influence.
Machine Learning 55(3): 251-270 (2004) |
| 2003 |
|---|
| 13 | EE | Marta Avalos,
Yves Grandvalet,
Christophe Ambroise:
Regularization Methods for Additive Models.
IDA 2003: 509-520 |
| 12 | EE | Yoshua Bengio,
Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation.
NIPS 2003 |
| 11 | EE | Jérémie François,
Yves Grandvalet,
Thierry Denoeux,
Jean-Michel Roger:
Resample and combine: an approach to improving uncertainty representation in evidential pattern classification.
Information Fusion 4(2): 75-85 (2003) |
| 10 | EE | Jérémie François,
Yves Grandvalet,
Thierry Denoeux,
Jean-Michel Roger:
Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification.
Information Fusion 4(3): 235-236 (2003) |
| 2002 |
|---|
| 9 | EE | Yves Grandvalet,
Stéphane Canu:
Adaptive Scaling for Feature Selection in SVMs.
NIPS 2002: 553-560 |
| 2001 |
|---|
| 8 | EE | Yves Grandvalet,
Florence d'Alché-Buc,
Christophe Ambroise:
Boosting Mixture Models for Semi-supervised Learning.
ICANN 2001: 41-48 |
| 7 | EE | Yves Grandvalet:
Bagging Can Stabilize without Reducing Variance.
ICANN 2001: 49-56 |
| 6 | EE | Florence d'Alché-Buc,
Yves Grandvalet,
Christophe Ambroise:
Semi-supervised MarginBoost.
NIPS 2001: 553-560 |
| 2000 |
|---|
| 5 | EE | Yves Grandvalet:
Bagging Down-Weights Leverage Points.
IJCNN (4) 2000: 505-510 |
| 1998 |
|---|
| 4 | EE | Yves Grandvalet,
Stéphane Canu:
Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage.
NIPS 1998: 445-451 |
| 1997 |
|---|
| 3 | | Skander Soltani,
Stéphane Canu,
Daniel Boichu,
Yves Grandvalet:
Wavelet Frames Based Estimator.
ICANN 1997: 319-324 |
| 2 | | Yves Grandvalet,
Stéphane Canu:
Adaptive Noise Injection for Input Variables Relevance Determination.
ICANN 1997: 463-468 |
| 1 | EE | Yves Grandvalet,
Stéphane Canu,
Stéphane Boucheron:
Noise Injection: Theoretical Prospects.
Neural Computation 9(5): 1093-1108 (1997) |
