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Antonio Orvieto
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Year
Learning explanations that are hard to vary
G Parascandolo, A Neitz, A Orvieto, L Gresele, B Schölkopf
International Conference on Learning Representations (2021), 2020
582020
A continuous-time perspective for modeling acceleration in Riemannian optimization
F Alimisis, A Orvieto, G Bécigneul, A Lucchi
International Conference on Artificial Intelligence and Statistics, 1297-1307, 2020
282020
Momentum improves optimization on Riemannian manifolds
F Alimisis, A Orvieto, G Becigneul, A Lucchi
International Conference on Artificial Intelligence and Statistics, 1351-1359, 2021
24*2021
Continuous-time models for stochastic optimization algorithms
A Orvieto, A Lucchi
Advances in Neural Information Processing Systems 32 (2019), 2018
182018
The role of memory in stochastic optimization
A Orvieto, J Kohler, A Lucchi
Uncertainty in Artificial Intelligence, 356-366, 2020
162020
An accelerated dfo algorithm for finite-sum convex functions
Y Chen, A Orvieto, A Lucchi
International Conference on Machine Learning (ICML), 2020, 2020
112020
Shadowing properties of optimization algorithms
A Orvieto, A Lucchi
Advances in Neural Information Processing Systems 32 (2019), 2019
112019
Faster single-loop algorithms for minimax optimization without strong concavity
J Yang, A Orvieto, A Lucchi, N He
International Conference on Artificial Intelligence and Statistics, 5485-5517, 2022
72022
Anticorrelated noise injection for improved generalization
A Orvieto, H Kersting, F Proske, F Bach, A Lucchi
arXiv preprint arXiv:2202.02831, 2022
52022
Vanishing Curvature in Randomly Initialized Deep ReLU Networks.
A Orvieto, J Kohler, D Pavllo, T Hofmann, A Lucchi
AISTATS, 7942-7975, 2022
2*2022
Two-Level K-FAC Preconditioning for Deep Learning
N Tselepidis, J Kohler, A Orvieto
NeurIPS 2020 Workshop on Optimization for Machine Learning (OPT2020), 2020
22020
Mean first exit times of Ornstein-Uhlenbeck processes in high-dimensional spaces
H Kersting, A Orvieto, F Proske, A Lucchi
arXiv preprint arXiv:2208.04029, 2022
12022
Explicit Regularization in Overparametrized Models via Noise Injection
A Orvieto, A Raj, H Kersting, F Bach
arXiv preprint arXiv:2206.04613, 2022
12022
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution
A Orvieto, S Lacoste-Julien, N Loizou
arXiv preprint arXiv:2205.04583, 2022
12022
Randomized Signature Layers for Signal Extraction in Time Series Data
E Monzio Compagnoni, L Biggio, A Orvieto, T Hofmann, J Teichmann
arXiv e-prints, arXiv: 2201.00384, 2022
1*2022
Rethinking the Variational Interpretation of Accelerated Optimization Methods
P Zhang, A Orvieto, H Daneshmand
Advances in Neural Information Processing Systems 34, 14396-14406, 2021
12021
On the Second-order Convergence Properties of Random Search Methods
A Lucchi, A Orvieto, A Solomou
Advances in Neural Information Processing Systems 34, 25633-25645, 2021
12021
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization
P Zhang, A Orvieto, H Daneshmand, T Hofmann, R Smith
International Conference on Artificial Intelligence and Statistics (2021), 2021
12021
On the Theoretical Properties of Noise Correlation in Stochastic Optimization
A Lucchi, F Proske, A Orvieto, F Bach, H Kersting
arXiv preprint arXiv:2209.09162, 2022
2022
Analysis and pharmacological modulation of senescence in human epithelial stem cells
V Barbaro, A Orvieto, G Alvisi, M Bertolin, F Bonelli, T Liehr, ...
Journal of Cellular and Molecular Medicine 26 (14), 3977-3994, 2022
2022
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