Cover Image

CMA Light: a novel Minibatch Algorithm for large-scale non convex finite sum optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Coppola, Corrado, Liuzzi, Giampaolo, Palagi, Laura
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for large-scale optimization
by: Coppola, Corrado, et al.
Published: (2024)

Convergence of ease-controlled Random Reshuffling gradient Algorithms under Lipschitz smoothness
by: Seccia, Ruggiero, et al.
Published: (2022)

Computational issues in Optimization for Deep networks
by: Coppola, Corrado, et al.
Published: (2024)

Worst-Case Complexity of High-Order Algorithms for Pareto-Front Reconstruction
by: Cristofari, Andrea, et al.
Published: (2025)

Worst-case complexity analysis of derivative-free methods for multi-objective optimization
by: Liuzzi, Giampaolo, et al.
Published: (2025)

Complexity results and active-set identification of a derivative-free method for bound-constrained problems
by: Brilli, Andrea, et al.
Published: (2024)

An interior point method for nonlinear constrained derivative-free optimization
by: Brilli, Andrea, et al.
Published: (2021)

Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search
by: Brilli, Andrea, et al.
Published: (2025)

Unboxing Tree Ensembles for interpretability: a hierarchical visualization tool and a multivariate optimal re-built tree
by: Di Teodoro, Giulia, et al.
Published: (2023)

Two-stage stochastic algorithm for solving large-scale (non)-convex separable optimization problems under affine constraints
by: Dubois-Taine, Benjamin, et al.
Published: (2026)

Worst case complexity bounds for linesearch-type derivative-free algorithms
by: Brilli, Andrea, et al.
Published: (2023)

GeNIOS: an (almost) second-order operator-splitting solver for large-scale convex optimization
by: Diamandis, Theo, et al.
Published: (2023)

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints
by: Lu, Zhaosong, et al.
Published: (2025)

Combinatorial Approaches for Embedded Feature Selection in Nonlinear SVMs
by: D'Onofrio, Federico, et al.
Published: (2025)

A linesearch-based derivative-free method for noisy black-box problems
by: De Santis, Alberto, et al.
Published: (2025)

A fast continuous time approach for non-smooth convex optimization with time scaling and Tikhonov regularization
by: Csetnek, Robert Ernö, et al.
Published: (2022)

Derivative-Free Bilevel Optimization with Inexact Lower-Level Solutions
by: Cesaroni, Edoardo, et al.
Published: (2026)

Benders decomposition for congested partial set covering location with uncertain demand
by: Calamita, Alice, et al.
Published: (2024)

Decentralized non-convex optimization via bi-level SQP and ADMM
by: Stomberg, Gösta, et al.
Published: (2022)

Robustness certificates in data-driven non-convex optimization with additively-uncertain constraints
by: Gallo, Alexander J, et al.
Published: (2026)

A flexible block-coordinate forward-backward algorithm for non-smooth and non-convex optimization
by: Briceño-Arias, Luis, et al.
Published: (2025)

Predefined-time distributed non-convex optimization via a time-base generator
by: Lin, Qinlong, et al.
Published: (2024)

Curse of scale-freeness: Intractability of large-scale optimization with multi-start methods
by: Masuyama, Hiroyuki, et al.
Published: (2022)

Theoretical analysis of the randomized subspace regularized Newton method for non-convex optimization
by: Fuji, Terunari, et al.
Published: (2022)

Hypodifferentials of nonsmooth convex functions and their applications to nonsmooth convex optimization
by: Dolgopolik, M. V.
Published: (2023)

Curvature accelerated decentralized non-convex optimization for high-dimensional machine learning problems
by: Yi, Dingran, et al.
Published: (2025)

The bilinear Hessian for large scale optimization
by: Carlsson, Marcus, et al.
Published: (2025)

Global and local approaches for the minimization of a sum of pointwise minima of convex functions
by: Van Dessel, Guillaume, et al.
Published: (2025)

Combining Gradient Information and Primitive Directions for High-Performance Mixed-Integer Optimization
by: Lapucci, Matteo, et al.
Published: (2024)

A systematic approach to general higher-order majorization-minimization algorithms for (non)convex optimization
by: Necoara, Ion, et al.
Published: (2020)

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

Strong duality in infinite convex optimization
by: Hantoute, Abderrahim, et al.
Published: (2025)

Fast and memory-efficient optimization for large-scale data-driven predictive control
by: Schmitz, Philipp, et al.
Published: (2024)

An accelerated proximal bundle method for convex optimization
by: Liao, Feng-Yi, et al.
Published: (2025)

A Minibatch-SGD-Based Learning Meta-Policy for Inventory Systems with Myopic Optimal Policy
by: Lyu, Jiameng, et al.
Published: (2024)

Stochastic maximum principle for optimal control problem with varying terminal time and non-convex control domain
by: Shi, Jin, et al.
Published: (2024)

Research on the descent direction of prediction correction algorithms for pseudo-convex/convex optimization problems
by: Li, Ting, et al.
Published: (2025)

Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization
by: Guigues, Vincent, et al.
Published: (2024)

Randomized gradient-free methods in convex optimization
by: Gasnikov, Alexander, et al.
Published: (2022)

Stochastic Maximum Principle for optimal advertising models with delay and non-convex control space
by: Guatteri, Giuseppina, et al.
Published: (2024)