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Antonio Orvieto
Antonio Orvieto
ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems
Verified email at tue.ellis.eu - Homepage
Title
Cited by
Cited by
Year
Resurrecting recurrent neural networks for long sequences
A Orvieto, SL Smith, A Gu, A Fernando, C Gulcehre, R Pascanu, S De
International Conference on Machine Learning, 26670-26698, 2023
1572023
Learning explanations that are hard to vary
G Parascandolo, A Neitz, A Orvieto, L Gresele, B Schölkopf
International Conference on Learning Representations (2021), 2020
1552020
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
612020
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
512022
Momentum improves optimization on Riemannian manifolds
F Alimisis, A Orvieto, G Becigneul, A Lucchi
International conference on artificial intelligence and statistics, 1351-1359, 2021
49*2021
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse
L Noci, S Anagnostidis, L Biggio, A Orvieto, SP Singh, A Lucchi
Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022
432022
Anticorrelated noise injection for improved generalization
A Orvieto, H Kersting, F Proske, F Bach, A Lucchi
International Conference on Machine Learning (ICML), 2022, 2022
382022
Continuous-time models for stochastic optimization algorithms
A Orvieto, A Lucchi
Advances in Neural Information Processing Systems 32 (2019), 2018
352018
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution
A Orvieto, S Lacoste-Julien, N Loizou
Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022
262022
The role of memory in stochastic optimization
A Orvieto, J Kohler, A Lucchi
Uncertainty in Artificial Intelligence, 356-366, 2020
242020
Explicit regularization in overparametrized models via noise injection
A Orvieto, A Raj, H Kersting, F Bach
International Conference on Artificial Intelligence and Statistics, 7265-7287, 2023
222023
Achieving a better stability-plasticity trade-off via auxiliary networks in continual learning
S Kim, L Noci, A Orvieto, T Hofmann
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
222023
Shadowing properties of optimization algorithms
A Orvieto, A Lucchi
Advances in Neural Information Processing Systems 32 (2019), 2019
212019
An accelerated dfo algorithm for finite-sum convex functions
Y Chen, A Orvieto, A Lucchi
International Conference on Machine Learning (ICML), 2020, 2020
192020
On the effectiveness of randomized signatures as reservoir for learning rough dynamics
EM Compagnoni, A Scampicchio, L Biggio, A Orvieto, T Hofmann, ...
2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023
16*2023
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
A Orvieto, S De, C Gulcehre, R Pascanu, SL Smith
Forty-first International Conference on Machine Learning, 2024
15*2024
An SDE for Modeling SAM: Theory and Insights
E Monzio Compagnoni, L Biggio, A Orvieto, FN Proske, H Kersting, ...
arXiv e-prints, arXiv: 2301.08203, 2023
15*2023
Vanishing Curvature in Randomly Initialized Deep ReLU Networks.
A Orvieto, J Kohler, D Pavllo, T Hofmann, A Lucchi
AISTATS, 7942-7975, 2022
15*2022
Theoretical Foundations of Deep Selective State-Space Models
N Muca Cirone, A Orvieto, B Walker, C Salvi, T Lyons
arXiv e-prints, arXiv: 2402.19047, 2024
11*2024
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
102021
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