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Valentina Zantedeschi
Valentina Zantedeschi
ServiceNow, Laval University
Adresse e-mail validée de servicenow.com - Page d'accueil
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Adversarial Robustness Toolbox v1. 0.0
N Maria-Irina, M Sinn, MN Tran, A Rawat, M Wistuba, V Zantedeschi, ...
arXiv preprint arXiv:1807.01069, 2018
630*2018
Efficient defenses against adversarial attacks
V Zantedeschi, MI Nicolae, A Rawat
Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017
3602017
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
872020
Lag-llama: Towards foundation models for time series forecasting
K Rasul, A Ashok, AR Williams, A Khorasani, G Adamopoulos, ...
arXiv preprint arXiv:2310.08278, 2023
462023
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
432022
RaVÆn: unsupervised change detection of extreme events using ML on-board satellites
V Růžička, A Vaughan, D De Martini, J Fulton, V Salvatelli, C Bridges, ...
Scientific reports 12 (1), 16939, 2022
35*2022
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
24*2021
Learning binary decision trees by argmin differentiation
V Zantedeschi, M Kusner, V Niculae
International Conference on Machine Learning, 12298-12309, 2021
23*2021
Causal discovery with language models as imperfect experts
S Long, A Piché, V Zantedeschi, T Schuster, A Drouin
Structured Probabilistic Inference & Generative Modeling (SPIGM) workshop at …, 2023
212023
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
212019
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, 455-467, 2021
182021
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
16*2016
Lag-llama: Towards foundation models for probabilistic time series forecasting
K Rasul, A Ashok, AR Williams, H Ghonia, R Bhagwatkar, A Khorasani, ...
Preprint, 2024
142024
Fast and provably effective multi-view classification with landmark-based svm
V Zantedeschi, R Emonet, M Sebban
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
122019
DAG learning on the permutahedron
V Zantedeschi, L Franceschi, J Kaddour, MJ Kusner, V Niculae
ICLR, 2023
92023
On margins and generalisation for voting classifiers
F Biggs, V Zantedeschi, B Guedj
Advances in Neural Information Processing Systems 35, 2022
92022
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
82020
TACTis-2: Better, faster, simpler attentional copulas for multivariate time series
A Ashok, É Marcotte, V Zantedeschi, N Chapados, A Drouin
arXiv preprint arXiv:2310.01327, 2023
72023
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
62016
Landmark-based ensemble learning with random Fourier features and gradient boosting
L Gautheron, P Germain, A Habrard, G Metzler, E Morvant, M Sebban, ...
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
5*2021
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