Imagen de Portada

The stochastic Ravine accelerated gradient method with general extrapolation coefficients

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Attouch, Hedy, Fadili, Jalal, Kungurtsev, Vyacheslav
Formato:	Preprint
Publicado:	2024
Materias:	Optimization and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

An SDE perspective on stochastic convex optimization
por: Maulen-Soto, Rodrigo, et al.
Publicado: (2022)

Stochastic Monotone Inclusion with Closed Loop Distributions
por: Ennaji, Hamza, et al.
Publicado: (2024)

Continuous Newton-like Methods featuring Inertia and Variable Mass
por: Castera, Camille, et al.
Publicado: (2023)

Inexact and Stochastic Gradient Optimization Algorithms with Inertia and Hessian Driven Damping
por: Choudhary, Harsh, et al.
Publicado: (2025)

Tikhonov Regularization for Stochastic Non-Smooth Convex Optimization in Hilbert Spaces
por: Maulen-Soto, Rodrigo, et al.
Publicado: (2024)

Quasi-Ergodic Control of Multi-Periodic Autoregressive Processes: Formulation and Examples
por: Kungurtsev, Vyacheslav
Publicado: (2025)

A Three-Tier Time-Scale Architecture for Controlling Complex Nonlinear Systems
por: Kungurtsev, Vyacheslav
Publicado: (2026)

An SDE Perspective on Stochastic Inertial Gradient Dynamics with Time-Dependent Viscosity and Geometric Damping
por: Maulen-Soto, Rodrigo, et al.
Publicado: (2024)

Stochastic Inertial Dynamics Via Time Scaling and Averaging
por: Maulen-Soto, Rodrigo, et al.
Publicado: (2024)

Convergence rates of regularized quasi-Newton methods without strong convexity
por: Wang, Shida, et al.
Publicado: (2025)

Mini-batch stochastic subgradient for functional constrained optimization
por: Singh, Nitesh Kumar, et al.
Publicado: (2024)

Global non-asymptotic super-linear convergence rates of regularized proximal quasi-Newton methods on non-smooth composite problems
por: Wang, Shida, et al.
Publicado: (2024)

Stochastic Approximation for Expectation Objective and Expectation Inequality-Constrained Nonconvex Optimization
por: Facchinei, Francisco, et al.
Publicado: (2023)

Multistage Stochastic Programming for Rare Event Risk Mitigation in Power Systems Management
por: Mastropietro, Daniel, et al.
Publicado: (2026)

A Quasi-Newton Primal-Dual Algorithm with Line Search
por: Wang, Shida, et al.
Publicado: (2024)

Inertial Quasi-Newton Methods for Monotone Inclusion: Efficient Resolvent Calculus and Primal-Dual Methods
por: Wang, Shida, et al.
Publicado: (2022)

Parallel variational quantum algorithms with gradient-informed restart to speed up optimisation in the presence of barren plateaus
por: Mastropietro, Daniel, et al.
Publicado: (2023)

Optimal Control of Two-Phase Membrane Problem
por: Bozorgnia, Farid, et al.
Publicado: (2024)

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
por: Sucker, Michael, et al.
Publicado: (2024)

Towards Tsallis Fully Probabilistic Design
por: Kungurtsev, Vyacheslav, et al.
Publicado: (2026)

Solution uniqueness of convex optimization problems via the radial cone
por: Fadili, Jalal, et al.
Publicado: (2024)

The Iterates of Nesterov's Accelerated Algorithm Converge in The Critical Regimes
por: Bot, Radu Ioan, et al.
Publicado: (2025)

Stochastic smoothing accelerated gradient method for general constrained nonsmooth convex composite optimization
por: Wang, Ruyu, et al.
Publicado: (2023)

Truss topology design under harmonic loads: Peak power minimization with semidefinite programming
por: Ma, Shenyuan, et al.
Publicado: (2024)

Parametric Semidefinite Programming: Geometry of the Trajectory of Solutions
por: Bellon, Antonio, et al.
Publicado: (2021)

Machine Learning Algorithms for Improving Exact Classical Solvers in Mixed Integer Continuous Optimization
por: Kimiaei, Morteza, et al.
Publicado: (2025)

Trilevel and Multilevel Optimization using Monotone Operator Theory
por: Shafiei, Allahkaram, et al.
Publicado: (2021)

Recovering Nesterov accelerated dynamics from Heavy Ball dynamics via time rescaling
por: Attouch, Hedy, et al.
Publicado: (2025)

Low Complexity Regularized Phase Retrieval
por: Godeme, Jean-Jacques, et al.
Publicado: (2024)

Direct-search methods for decentralized blackbox optimization
por: Bergou, El Houcine, et al.
Publicado: (2025)

Tame Riemannian Stochastic Approximation
por: Aspman, Johannes, et al.
Publicado: (2023)

Unifying restart accelerated gradient and proximal bundle methods
por: Liang, Jiaming
Publicado: (2025)

A class of generalized Nesterov's accelerated gradient method from dynamical perspective
por: Cheng, Xu, et al.
Publicado: (2025)

A nonmonotone extrapolated proximal gradient-subgradient algorithm beyond global Lipschitz gradient continuity
por: Yang, Lei, et al.
Publicado: (2025)

Fast convex optimization via closed-loop time scaling of gradient dynamics
por: Attouch, Hedy, et al.
Publicado: (2023)

Probabilistic Iterative Hard Thresholding for Sparse Learning
por: Bergamaschi, Matteo, et al.
Publicado: (2024)

Towards Real Time Control of Water Engineering with Nonlinear Hyperbolic Partial Differential Equations
por: DiFonzo, Fabio, et al.
Publicado: (2025)

Stochastic Langevin Differential Inclusions with Applications to Machine Learning
por: Difonzo, Fabio V., et al.
Publicado: (2022)

Iteration Complexity of Variational Quantum Algorithms
por: Kungurtsev, Vyacheslav, et al.
Publicado: (2022)

Efficiency of stochastic coordinate proximal gradient methods on nonseparable composite optimization
por: Necoara, I., et al.
Publicado: (2021)