default search action
Antonio Orvieto
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c24]Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurélien Lucchi:
SDEs for Minimax Optimization. AISTATS 2024: 4834-4842 - [c23]Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann:
Recurrent Distance Filtering for Graph Representation Learning. ICML 2024 - [c22]Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L. Smith:
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues. ICML 2024 - [i31]Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Norbert Proske, Aurélien Lucchi:
SDEs for Minimax Optimization. CoRR abs/2402.12508 (2024) - [i30]Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto:
Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning. CoRR abs/2402.17457 (2024) - [i29]Nicola Muca Cirone, Antonio Orvieto, Benjamin Walker, Cristopher Salvi, Terry J. Lyons:
Theoretical Foundations of Deep Selective State-Space Models. CoRR abs/2402.19047 (2024) - [i28]Diganta Misra, Jay Gala, Antonio Orvieto:
On the low-shot transferability of [V]-Mamba. CoRR abs/2403.10696 (2024) - [i27]Jerome Sieber, Carmen Amo Alonso, Alexandre Didier
, Melanie N. Zeilinger, Antonio Orvieto:
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks. CoRR abs/2405.15731 (2024) - [i26]Nicolas Zucchet, Antonio Orvieto:
Recurrent neural networks: vanishing and exploding gradients are not the end of the story. CoRR abs/2405.21064 (2024) - [i25]Si Yi Meng, Antonio Orvieto, Daniel Yiming Cao, Christopher De Sa:
Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes. CoRR abs/2406.05033 (2024) - [i24]Antonio Orvieto, Lin Xiao:
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes. CoRR abs/2407.04358 (2024) - [i23]Sajad Movahedi, Antonio Orvieto, Seyed-Mohsen Moosavi-Dezfooli:
Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture. CoRR abs/2410.12025 (2024) - [i22]Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi:
Loss Landscape Characterization of Neural Networks without Over-Parametrization. CoRR abs/2410.12455 (2024) - [i21]Nursena Köprücü, Destiny Okpekpe, Antonio Orvieto:
NIMBA: Towards Robust and Principled Processing of Point Clouds With SSMs. CoRR abs/2411.00151 (2024) - 2023
- [c21]Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach:
Explicit Regularization in Overparametrized Models via Noise Injection. AISTATS 2023: 7265-7287 - [c20]Sanghwan Kim, Lorenzo Noci, Antonio Orvieto, Thomas Hofmann:
Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning. CVPR 2023: 11930-11939 - [c19]Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi:
An SDE for Modeling SAM: Theory and Insights. ICML 2023: 25209-25253 - [c18]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De:
Resurrecting Recurrent Neural Networks for Long Sequences. ICML 2023: 26670-26698 - [c17]Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann:
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics. IJCNN 2023: 1-8 - [i20]Enea Monzio Compagnoni
An SDE for Modeling SAM: Theory and Insights. CoRR abs/2301.08203 (2023) - [i19]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre
Resurrecting Recurrent Neural Networks for Long Sequences. CoRR abs/2303.06349 (2023) - [i18]Sanghwan Kim, Lorenzo Noci, Antonio Orvieto, Thomas Hofmann:
Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning. CoRR abs/2303.09483 (2023) - [i17]Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith:
On the Universality of Linear Recurrences Followed by Nonlinear Projections. CoRR abs/2307.11888 (2023) - [i16]Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann:
Recurrent Distance-Encoding Neural Networks for Graph Representation Learning. CoRR abs/2312.01538 (2023) - 2022
- [c16]Junchi Yang, Antonio Orvieto, Aurélien Lucchi, Niao He:
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. AISTATS 2022: 5485-5517 - [c15]Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurélien Lucchi:
Vanishing Curvature in Randomly Initialized Deep ReLU Networks. AISTATS 2022: 7942-7975 - [c14]Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi:
Anticorrelated Noise Injection for Improved Generalization. ICML 2022: 17094-17116 - [c13]Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting:
On the Theoretical Properties of Noise Correlation in Stochastic Optimization. NeurIPS 2022 - [c12]Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi:
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. NeurIPS 2022 - [c11]Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou:
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution. NeurIPS 2022 - [i15]Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann:
Randomized Signature Layers for Signal Extraction in Time Series Data. CoRR abs/2201.00384 (2022) - [i14]Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi:
Anticorrelated Noise Injection for Improved Generalization. CoRR abs/2202.02831 (2022) - [i13]Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. CoRR abs/2206.03126 (2022) - [i12]Antonio Orvieto, Anant Raj
Explicit Regularization in Overparametrized Models via Noise Injection. CoRR abs/2206.04613 (2022) - [i11]Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting:
On the Theoretical Properties of Noise Correlation in Stochastic Optimization. CoRR abs/2209.09162 (2022) - 2021
- [c10]Foivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi:
Momentum Improves Optimization on Riemannian Manifolds. AISTATS 2021: 1351-1359 - [c9]Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith:
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization. AISTATS 2021: 3979-3987 - [c8]Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf:
Learning explanations that are hard to vary. ICLR 2021 - [c7]Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand:
Rethinking the Variational Interpretation of Accelerated Optimization Methods. NeurIPS 2021: 14396-14406 - [c6]Aurélien Lucchi, Antonio Orvieto, Adamos Solomou:
On the Second-order Convergence Properties of Random Search Methods. NeurIPS 2021: 25633-25645 - [i10]Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith:
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization. CoRR abs/2102.11537 (2021) - [i9]Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurélien Lucchi:
Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks. CoRR abs/2106.03763 (2021) - [i8]Aurélien Lucchi, Antonio Orvieto, Adamos Solomou:
On the Second-order Convergence Properties of Random Search Methods. CoRR abs/2110.13265 (2021) - [i7]Junchi Yang, Antonio Orvieto, Aurélien Lucchi, Niao He:
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. CoRR abs/2112.05604 (2021) - 2020
- [c5]Foivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi:
A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization. AISTATS 2020: 1297-1307 - [c4]Yuwen Chen, Antonio Orvieto, Aurélien Lucchi:
An Accelerated DFO Algorithm for Finite-sum Convex Functions. ICML 2020: 1681-1690 - [i6]Yuwen Chen, Antonio Orvieto, Aurélien Lucchi:
An Accelerated DFO Algorithm for Finite-sum Convex Functions. CoRR abs/2007.03311 (2020) - [i5]Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf:
Learning explanations that are hard to vary. CoRR abs/2009.00329 (2020) - [i4]Nikolaos Tselepidis, Jonas Kohler, Antonio Orvieto:
Two-Level K-FAC Preconditioning for Deep Learning. CoRR abs/2011.00573 (2020)
2010 – 2019
- 2019
- [c3]Antonio Orvieto, Aurélien Lucchi:
Continuous-time Models for Stochastic Optimization Algorithms. NeurIPS 2019: 12589-12601 - [c2]Antonio Orvieto, Aurélien Lucchi:
Shadowing Properties of Optimization Algorithms. NeurIPS 2019: 12671-12682 - [c1]Antonio Orvieto, Jonas Kohler, Aurélien Lucchi:
The Role of Memory in Stochastic Optimization. UAI 2019: 356-366 - [i3]Antonio Orvieto, Jonas Kohler, Aurélien Lucchi:
The Role of Memory in Stochastic Optimization. CoRR abs/1907.01678 (2019) - [i2]Antonio Orvieto, Aurélien Lucchi:
Shadowing Properties of Optimization Algorithms. CoRR abs/1911.05206 (2019) - 2018
- [i1]Antonio Orvieto, Aurélien Lucchi:
Continuous-time Models for Stochastic Optimization Algorithms. CoRR abs/1810.02565 (2018)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-11 20:46 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: