Valentina Zantedeschi
Valentina Zantedeschi
Postdoctoral research fellow at Inria and University College London
Geverifieerd e-mailadres voor inria.fr - Homepage
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Adversarial Robustness Toolbox v0. 2.2
MI Nicolae, M Sinn, TN Minh, A Rawat, M Wistuba, V Zantedeschi, ...
204*2018
Efficient defenses against adversarial attacks
V Zantedeschi, MI Nicolae, A Rawat
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017
2012017
Fully decentralized joint learning of personalized models and collaboration graphs
V Zantedeschi, A Bellet, M Tommasi
International Conference on Artificial Intelligence and Statistics, 864-874, 2020
152020
Metric learning as convex combinations of local models with generalization guarantees
V Zantedeschi, R Emonet, M Sebban
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
132016
Cumulo: A Dataset for Learning Cloud Classes
V Zantedeschi, F Falasca, A Douglas, R Strange, MJ Kusner, ...
Tackling Climate Change with Machine Learning, NeurIPS 2019 Workshop, 2019
72019
Fast and provably effective multi-view classification with landmark-based svm
V Zantedeschi, R Emonet, M Sebban
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
72018
Beta-risk: a new surrogate risk for learning from weakly labeled data
V Zantedeschi, R Emonet, M Sebban
Advances in Neural Information Processing Systems, 4365-4373, 2016
62016
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery
CS de Witt, C Tong, V Zantedeschi, D De Martini, A Kalaitzis, M Chantry, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 14902 …, 2021
4*2021
Communication-efficient and decentralized multi-task boosting while learning the collaboration graph
V Zantedeschi, A Bellet, M Tommasi
32019
L3-SVMs: Landmarks-based linear local support vectors machines
V Zantedeschi, R Emonet, M Sebban
32017
Learning Binary Decision Trees by Argmin Differentiation
V Zantedeschi, M Kusner, V Niculae
International Conference on Machine Learning, 12298-12309, 2021
2*2021
Landmark-based ensemble learning with random Fourier features and gradient boosting
L Gautheron, P Germain, A Habrard, G Metzler, E Morvant, M Sebban, ...
European Conference on Machine Learning and Principles and Practice of …, 2020
22020
Towards data-driven physics-informed global precipitation forecasting from satellite imagery
V Zantedeschi, D De Martini, C Tong, CS de Witt, A Kalaitzis, M Chantry, ...
Proceedings of the AI for Earth Sciences Workshop at NeurIPS, 2020
22020
Revisite des" random Fourier features" basée sur l'apprentissage PAC-Bayésien via des points d'intérêts
L Gautheron, P Germain, A Habrard, G Letarte, E Morvant, M Sebban, ...
CAp 2019-Conférence sur l'Apprentissage automatique, 2019
22019
A Unified View of Local Learning: Theory and Algorithms for Enhancing Linear Models
V Zantedeschi
Université de Lyon, 2018
12018
Apprentissage de combinaisons convexes de métriques locales avec garanties de généralisation
V Zantedeschi, R Emonet, M Sebban
CAp2016, 2016
12016
Lipschitz continuity of mahalanobis distances and bilinear forms
V Zantedeschi, R Emonet, M Sebban
arXiv preprint arXiv:1604.01376, 2016
12016
Apprentissage d'ensemble basé sur des points de repère avec des caractéristiques de Fourier aléatoires et un renforcement du gradient
L Gautheron, P Germain, A Habrard, G Metzler, E Morvant, M Sebban, ...
Conférence sur l'Apprentissage automatique (CAp), 2020a.(Cited on pages 5 …, 0
1
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
V Zantedeschi, P Viallard, E Morvant, R Emonet, A Habrard, P Germain, ...
arXiv preprint arXiv:2106.12535, 2021
2021
RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale
C Schroeder de Witt, C Tong, V Zantedeschi, D De Martini, A Kalaitzis, ...
EGU General Assembly Conference Abstracts, EGU21-1762, 2021
2021
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