Cover Image

Holonorm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yongueng, Daryl Noupa, Tembine, Hamidou
Format:	Preprint
Published:	2025
Subjects:	Machine Learning 68T07 (Primary), 65K10, 90C30 (Secondary)
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning
by: Liu, Yaru, et al.
Published: (2026)

Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization
by: DePavia, Adela, et al.
Published: (2025)

Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks
by: Li, Minshuo, et al.
Published: (2026)

SVD-Preconditioned Gradient Descent Method for Solving Nonlinear Least Squares Problems
by: Chang, Zhipeng, et al.
Published: (2026)

Sample-wise Constrained Learning via a Sequential Penalty Approach with Applications in Image Processing
by: Lanzillotta, Francesca, et al.
Published: (2026)

Error Bound Analysis for the Regularized Loss of Deep Linear Neural Networks
by: Chen, Po, et al.
Published: (2025)

Cascade Token Selection for Transformer Attention Acceleration
by: Thomas, Stephen J.
Published: (2026)

Gated Subspace Inference for Transformer Acceleration
by: Thomas, Stephen J.
Published: (2026)

Effectively Leveraging Momentum Terms in Stochastic Line Search Frameworks for Fast Optimization of Finite-Sum Problems
by: Lapucci, Matteo, et al.
Published: (2024)

Convergence Conditions for Stochastic Line Search Based Optimization of Over-parametrized Models
by: Lapucci, Matteo, et al.
Published: (2024)

Power Homotopy for Zeroth-Order Non-Convex Optimizations
by: Xu, Chen
Published: (2025)

Global Optimization with A Power-Transformed Objective and Gaussian Smoothing
by: Xu, Chen
Published: (2024)

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
by: Visentin, Gabriele, et al.
Published: (2025)

Relaxed Weak Accelerated Proximal Gradient Method: a Unified Framework for Nesterov's Accelerations
by: Li, Hongda, et al.
Published: (2025)

Preconditioned subgradient method for composite optimization: overparameterization and fast convergence
by: Díaz, Mateo, et al.
Published: (2025)

An Augmented Lagrangian Method for Training Recurrent Neural Networks
by: Wang, Yue, et al.
Published: (2024)

Derivative-Informed Fourier Neural Operator: Universal Approximation and Applications to PDE-Constrained Optimization
by: Yao, Boyuan, et al.
Published: (2025)

Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
by: Troxell, David, et al.
Published: (2026)

Progressive Power Homotopy for Non-convex Optimization
by: Xu, Chen
Published: (2026)

Error bounds for Physics Informed Neural Networks in Generalized KdV Equations placed on unbounded domains
by: Freire, Ricardo, et al.
Published: (2026)

Refining Graphical Neural Network Predictions Using Flow Matching for Optimal Power Flow with Constraint-Satisfaction Guarantee
by: Khanal, Kshitiz
Published: (2025)

Local properties of neural networks through the lens of layer-wise Hessians
by: Bolshim, Maxim, et al.
Published: (2025)

Inter-Layer Hessian Analysis of Neural Networks with DAG Architectures
by: Bolshim, Maxim, et al.
Published: (2026)

Stochastic Estimation of the Layer-wise Hessian Trace for Monitoring Neural-network Training
by: Bolshim, Maxim, et al.
Published: (2026)

On the boundedness of the sequence generated by minibatch stochastic gradient descent
by: Bauschke, Heinz H., et al.
Published: (2025)

Rank-one Riemannian Subspace Descent for Nonlinear Matrix Equations
by: Darmwal, Yogesh, et al.
Published: (2026)

On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent
by: Laumont, Rémi, et al.
Published: (2022)

Parameter-free accelerated gradient descent for nonconvex minimization
by: Marumo, Naoki, et al.
Published: (2022)

Accelerated-gradient-based generalized Levenberg--Marquardt method with oracle complexity bound and local quadratic convergence
by: Marumo, Naoki, et al.
Published: (2022)

Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth
by: Davis, Damek, et al.
Published: (2024)

Entropic Mirror Descent for Linear Systems: Polyak's Stepsize and Implicit Bias
by: Malitsky, Yura, et al.
Published: (2025)

Image Restoration Models with Optimal Transport and Total Variation Regularization
by: Huang, Weijia, et al.
Published: (2025)

Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
by: Xie, Pengcheng, et al.
Published: (2025)

Curves of Minimax Spirality
by: Kaya, C. Yalçın, et al.
Published: (2024)

Convergence of gradient descent for deep neural networks
by: Chatterjee, Sourav
Published: (2022)

Learning to Integrate
by: Ernst, Oliver G., et al.
Published: (2025)

Error bounds for Physics Informed Neural Networks in Nonlinear Schrödinger equations placed on unbounded domains
by: Alejo, Miguel Á., et al.
Published: (2024)

Benchmarking Generative AI Against Bayesian Optimization for Constrained Multi-Objective Inverse Design
by: Awan, Muhammad Bilal, et al.
Published: (2025)

Deep Legendre Transform
by: Minabutdinov, Aleksey, et al.
Published: (2025)

An Analysis of Optimizer Choice on Energy Efficiency and Performance in Neural Network Training
by: Almog, Tom
Published: (2025)