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Marc Sebban
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Publications
- 2023
- [c73]Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban:
Is My Neural Net Driven by the MDL Principle? ECML/PKDD (2) 2023: 173-189 - 2022
- [j33]Eduardo Brandao, Jean-Philippe Colombier, Stefan Duffner, Rémi Emonet, Florence Garrelie, Amaury Habrard, François Jacquenet, Anthony Nakhoul, Marc Sebban:
Learning PDE to Model Self-Organization of Matter. Entropy 24(8): 1096 (2022) - [c71]Tanguy Kerdoncuff, Rémi Emonet, Michaël Perrot, Marc Sebban:
Optimal Tensor Transport. AAAI 2022: 7124-7132 - 2021
- [j31]Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban:
A Nearest Neighbor Algorithm for Imbalanced Classification. Int. J. Artif. Intell. Tools 30(3): 2150013:1-2150013:27 (2021) - [j30]Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban:
Sampled Gromov Wasserstein. Mach. Learn. 110(8): 2151-2186 (2021) - 2020
- [c67]Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban:
A Swiss Army Knife for Minimax Optimal Transport. ICML 2020: 2504-2513 - [c66]Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban:
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. IJCAI 2020: 2155-2161 - [c65]Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban:
Metric Learning in Optimal Transport for Domain Adaptation. IJCAI 2020: 2162-2168 - 2019
- [c62]Kevin Bascol, Rémi Emonet, Élisa Fromont, Amaury Habrard, Guillaume Metzler, Marc Sebban:
From Cost-Sensitive to Tight F-measure Bounds. AISTATS 2019: 1245-1253 - [c61]Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban:
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. ICTAI 2019: 243-250 - [i9]Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban:
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. CoRR abs/1909.00693 (2019) - 2018
- [c55]Valentina Zantedeschi, Rémi Emonet, Marc Sebban:
Fast and Provably Effective Multi-view Classification with Landmark-Based SVM. ECML/PKDD (2) 2018: 193-208 - 2017
- [p1]Basura Fernando, Rahaf Aljundi, Rémi Emonet, Amaury Habrard, Marc Sebban, Tinne Tuytelaars:
Unsupervised Domain Adaptation Based on Subspace Alignment. Domain Adaptation in Computer Vision Applications 2017: 81-94 - [i7]Valentina Zantedeschi, Rémi Emonet, Marc Sebban:
L3-SVMs: Landmarks-based Linear Local Support Vectors Machines. CoRR abs/1703.00284 (2017) - 2016
- [c52]Valentina Zantedeschi, Rémi Emonet, Marc Sebban:
Metric Learning as Convex Combinations of Local Models with Generalization Guarantees. CVPR 2016: 1478-1486 - [c51]Valentina Zantedeschi, Rémi Emonet, Marc Sebban:
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data. NIPS 2016: 4358-4366 - [i6]Valentina Zantedeschi, Rémi Emonet, Marc Sebban:
Lipschitz Continuity of Mahalanobis Distances and Bilinear Forms. CoRR abs/1604.01376 (2016) - 2015
- [c49]Rahaf Aljundi, Rémi Emonet, Damien Muselet, Marc Sebban:
Landmarks-based kernelized subspace alignment for unsupervised domain adaptation. CVPR 2015: 56-63
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