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Antonio Silveti-Falls

Training Deep Learning Models with Norm-Constrained LMOs
2025 · Pethick, Thomas, Xie, Wanyun, et al. · arXiv (Cornell University) · 121
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Nonsmooth Implicit Differentiation for Machine Learning and Optimization
2021 · Bolte, Jérôme, Le, Tam, et al. · arXiv (Cornell University) · 27
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Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems
2024 · Jérôme Bolte, Edouard Pauwels, et al. · SIAM Journal on Optimization · 19
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Generalized Conditional Gradient with Augmented Lagrangian for Composite Minimization
2020 · Antonio Silveti-Falls, Cesare Molinari, et al. · SIAM Journal on Optimization · 16
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Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness
2025 · Pethick, Thomas, Xie, Wanyun, et al. · arXiv (Cornell University) · 14
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Inexact and Stochastic Generalized Conditional Gradient with Augmented Lagrangian and Proximal Step
2021 · Antonio Silveti-Falls, Cesare Molinari, et al. · Journal of Nonsmooth Analysis and Optimization · 7
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A Stochastic Bregman Primal-Dual Splitting Algorithm for Composite Optimization
2021 · Silveti-Falls, Antonio, Molinari, Cesare, et al. · arXiv (Cornell University) · 6
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Training Neural Networks at Any Scale: An exposition
2026 · Thomas Pethick, Kimon Antonakopoulos, et al. · IEEE Signal Processing Magazine · 5
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On the Role of Batch Size in Stochastic Conditional Gradient Methods
2026 · Islamov, Rustem, Machacek, Roman, et al. · arXiv (Cornell University) · 5
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Adaptive Conditional Gradient Descent
2025 · Khademi, Abbas, Silveti-Falls, Antonio · arXiv (Cornell University) · 4
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Frank-Wolfe with Moreau Envelope Smoothing for Nonsmooth Nonconvex Problems
2026 · Silveti-Falls, Antonio, Molinari, Cesare, et al. · arXiv (Cornell University) · 2
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Boosted Stochastic Frank-Wolfe for Constrained Nonconvex Optimization
2026 · Nandhan, Navil, Khademi, Abbas, et al. · arXiv (Cornell University) · 1
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Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
2026 · Oikonomidis, Konstantinos, Quan, Jan, et al. · arXiv (Cornell University) · 1
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Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness
2025 · Thomas Pethick, Wanyun Xie, et al. · neural information processing systems · 1
ClippedScion: Generalized Gradient Norm Clipping and Non-Euclidean (L0, L1)-Smoothness
2026 · Pethick, Thomas, Xie, Wanyun, et al. · Zenodo (CERN European Organization for Nuclear Research)
Scion: Training Deep Learning Models with Norm-Constrained LMOs
2026 · Pethick, Thomas, Xie, Wanyun, et al. · Zenodo (CERN European Organization for Nuclear Research)
Differentiating Minimal-Norm Solutions to Parametric Optimization Problems
2026 · Plaquevent-Jourdain, Baptiste, Fadili, Jalal, et al. · arXiv (Cornell University)
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Numerical Implementation of Variational Morphological Operators on Graphs
2025 · Miguel Amorim, Jean-Christophe Pesquet, et al. · Lecture notes in computer science
First-order noneuclidean splitting methods for large-scale optimization : deterministic and stochastic algorithms
2021 · Antonio Silveti-Falls · HAL
First-order noneuclidean splitting methods for large-scale optimization : deterministic and stochastic algorithms
2021 · Antonio Silveti Falls · theses.fr (ABES)
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Gradient conditionnel généralisé et lagrangien augmenté pour la minimisation composite
2019 · Silveti-Falls, Antonio, Molinari, Cesare, et al. · HAL
Generalized Conditional Gradient with Augmented Lagrangian for Composite Optimization
2019 · Silveti-Falls, Antonio, Molinari, Cesare, et al. · HAL
Works count: 22
Citation count: 229
H-index: 6
I10-index: 5
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