:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Buck, Kevin, Babyak, Jessica, Piersanti, Paolo, Zumbrun, Kevin, Gallos, Christiane, Gallos, Dorothea
Format:	Preprint
Publié:	2025
Sujets:	Optimization and Control
Accès en ligne:	https://arxiv.org/abs/2503.02155
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Sychronous vs. asynchronous coalitions in multiplayer games, with applications to guts poker
par: Babyak, Jessica, et autres
Publié: (2024)

On the convergence analysis of the decentralized projected gradient descent method
par: Choi, Woocheol, et autres
Publié: (2023)

Almost sure convergence of stochastic Hamiltonian descent methods
par: Williamson, Måns, et autres
Publié: (2024)

Non-convergence to global minimizers for Adam and stochastic gradient descent optimization and constructions of local minimizers in the training of artificial neural networks
par: Jentzen, Arnulf, et autres
Publié: (2024)

Non-smooth stochastic gradient descent using smoothing functions
par: Giovannelli, Tommaso, et autres
Publié: (2025)

Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization
par: Dambrine, Marc, et autres
Publié: (2024)

Mirror descent method for stochastic multi-objective optimization
par: Yang, Linxi, et autres
Publié: (2024)

New logarithmic step size for stochastic gradient descent
par: Shamaee, M. Soheil, et autres
Publié: (2024)

Global convergence of gradient descent for phase retrieval
par: Fougereux, Théodore, et autres
Publié: (2024)

Worst-case convergence analysis of relatively inexact gradient descent on smooth convex functions
par: Vernimmen, Pierre, et autres
Publié: (2025)

Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
par: Stollenwerk, Alexander, et autres
Publié: (2024)

Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
par: Dereich, Steffen, et autres
Publié: (2024)

On the global convergence of gradient descent for wide shallow models with bounded nonlinearities
par: Petit, Romain, et autres
Publié: (2026)

Proximal gradient-type method with generalized distance and convergence analysis without global descent lemma
par: Yagishita, Shotaro, et autres
Publié: (2025)

A stochastic gradient descent algorithm with random search directions
par: Gbaguidi, Eméric
Publié: (2025)

A global Barzilai and Borwein's gradient normalization descent method for multiobjective optimization
par: Yang, Yingxue
Publié: (2024)

Convergence of continuous-time stochastic gradient descent with applications to deep neural networks
par: Lugosi, Gabor, et autres
Publié: (2024)

Implicit regularization of normalized gradient descent
par: Josz, Cédric
Publié: (2026)

Adaptive control mechanisms in gradient descent algorithms
par: Iannelli, Andrea
Publié: (2025)

Introduction: Swarm-based gradient descent for non convex optimization
par: Tikko, Janina
Publié: (2024)

Almost sure convergence rates of stochastic gradient methods under gradient domination
par: Weissmann, Simon, et autres
Publié: (2024)

On the convergence of conditional gradient method for unbounded multiobjective optimization problems
par: Chen, Wang, et autres
Publié: (2024)

A consensus-based optimization method for nonsmooth nonconvex programs with approximated gradient descent scheme
par: Wei, Jiazhen, et autres
Publié: (2025)

Fast Spawn\&Prune (FS\&P): Global convergence of stochastic conic particle gradient descent via birth/death process
par: De Castro, Yohann, et autres
Publié: (2026)

Exponential convergence rates for momentum stochastic gradient descent in the overparametrized setting
par: Gess, Benjamin, et autres
Publié: (2023)

On the convergence of stochastic variance reduced gradient for linear inverse problems
par: Jin, Bangti, et autres
Publié: (2025)

Mirror descent for constrained stochastic control problems
par: Sethi, Deven, et autres
Publié: (2025)

PL conditions do not guarantee convergence of gradient descent-ascent dynamics
par: Mourrat, Jean-Christophe
Publié: (2026)

Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks
par: An, Jing, et autres
Publié: (2023)

Learning complexity of gradient descent and conjugate gradient algorithms
par: Jiao, Xianqi, et autres
Publié: (2024)

Equilibrium convergence in large games
par: Chen, Enxian, et autres
Publié: (2020)

Exact worst-case convergence rates of gradient descent: a complete analysis for all constant stepsizes over nonconvex and convex functions
par: Rotaru, Teodor, et autres
Publié: (2024)

A stochastic gradient method for trilevel optimization
par: Giovannelli, Tommaso, et autres
Publié: (2025)

Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms
par: Simon, Emile, et autres
Publié: (2011)

A short proof of near-linear convergence of adaptive gradient descent under fourth-order growth and convexity
par: Davis, Damek, et autres
Publié: (2026)

Efficiency of stochastic coordinate proximal gradient methods on nonseparable composite optimization
par: Necoara, I., et autres
Publié: (2021)

Explicit solution to an optimal two-player switching game in infinite horizon
par: Asri, Brahim El, et autres
Publié: (2024)

Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
par: Quiroga, David A., et autres
Publié: (2023)

Dealing with unbounded gradients in stochastic saddle-point optimization
par: Neu, Gergely, et autres
Publié: (2024)

Local convergence of mean-field Langevin dynamics: from gradient flows to linearly monotone games
par: Wang, Guillaume, et autres
Publié: (2026)