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Valentina Zantedeschi
Valentina Zantedeschi
Postdoctoral researcher at Inria and University College London
Adresse e-mail validée de inria.fr - Page d'accueil
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Adversarial Robustness Toolbox v0. 2.2
MI Nicolae, M Sinn, TN Minh, A Rawat, M Wistuba, V Zantedeschi, ...
260*2018
Efficient defenses against adversarial attacks
V Zantedeschi, MI Nicolae, A Rawat
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017
2372017
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
302020
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
102019
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
82018
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
7*2021
Beta-risk: a new surrogate risk for learning from weakly labeled data
V Zantedeschi, R Emonet, M Sebban
Advances in Neural Information Processing Systems 29, 2016
52016
Learning Binary Decision Trees by Argmin Differentiation
V Zantedeschi, M Kusner, V Niculae
International Conference on Machine Learning, 12298-12309, 2021
4*2021
L3-SVMs: Landmarks-based linear local support vectors machines
V Zantedeschi, R Emonet, M Sebban
32017
Landmark-based ensemble learning with random Fourier features and gradient boosting
L Gautheron, P Germain, A Habrard, G Metzler, E Morvant, M Sebban, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
2*2020
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
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
V Zantedeschi, P Viallard, E Morvant, R Emonet, A Habrard, P Germain, ...
Advances in Neural Information Processing Systems 34, 2021
12021
A Unified View of Local Learning: Theory and Algorithms for Enhancing Linear Models
V Zantedeschi
Université de Lyon, 2018
12018
Lipschitz continuity of mahalanobis distances and bilinear forms
V Zantedeschi, R Emonet, M Sebban
arXiv preprint arXiv:1604.01376, 2016
12016
Insights from an autism imaging biomarker challenge: promises and threats to biomarker discovery
N Traut, K Heuer, G Lemaître, A Beggiato, D Germanaud, M Elmaleh, ...
NeuroImage 255, 119171, 2022
2022
DAG Learning on the Permutahedron
V Zantedeschi, J Kaddour, L Franceschi, M Kusner, V Niculae
ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality, 2022
2022
Unsupervised Change Detection of Extreme Events Using ML On-Board
V Růžička, A Vaughan, D De Martini, J Fulton, V Salvatelli, C Bridges, ...
arXiv preprint arXiv:2111.02995, 2021
2021
Communication-Efficient Decentralized Boosting while Discovering the Collaboration Graph
V Zantedeschi, A Bellet, M Tommasi
NeurIPS 2018-Workshop on Machine Learning on the Phone and other Consumer …, 2018
2018
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