Cover Image

PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Shenghao, Wang, Zhichao, Balabanov, Oleg, Erichson, N. Benjamin, Mahoney, Michael W.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Numerical Analysis Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient nonlocal linear image denoising: Bilevel optimization with Nonequispaced Fast Fourier Transform and matrix-free preconditioning
by: Miniguano-Trujillo, Andrés, et al.
Published: (2024)

The Dynamical Anatomy of Anderson Acceleration:From Adaptive Momentum to Variable-Mass ODEs
by: Chen, Kewang, et al.
Published: (2025)

Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
by: Niu, Chengmei, et al.
Published: (2025)

The Generalized Matrix Separation Problem: Algorithms
by: Chen, Xuemei, et al.
Published: (2025)

Anderson-type acceleration method for Deep Neural Network optimization
by: Ito, Kazufumi, et al.
Published: (2025)

Spiking Neural Networks: a theoretical framework for Universal Approximation and training
by: Biccari, Umberto
Published: (2025)

A Unified Phase-Field Fourier Neural Network Framework for Topology Optimization
by: Li, Jing, et al.
Published: (2025)

Efficient Solution of State-Constrained Distributed Parabolic Optimal Control Problems
by: Löscher, Richard, et al.
Published: (2024)

Accelerating operator Sinkhorn iteration with overrelaxation
by: Soma, Tasuku, et al.
Published: (2024)

AutoBalance: An Automatic Balancing Framework for Training Physics-Informed Neural Networks
by: An, Kang, et al.
Published: (2025)

Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
by: Fang, Yuchen, et al.
Published: (2024)

Fast and Numerically Stable Implementation of Rate Constant Matrix Contraction Method
by: Hemmi, Shinichi, et al.
Published: (2024)

Block Matrix and Tensor Randomized Kaczmarz Methods for Linear Feasibility Problems
by: Zhang, Minxin, et al.
Published: (2024)

Numerical Analysis on Neural Network Projected Schemes for Approximating One Dimensional Wasserstein Gradient Flows
by: Zuo, Xinzhe, et al.
Published: (2024)

A Lyapunov Analysis of Accelerated PDHG Algorithms
by: Zeng, Xueying, et al.
Published: (2024)

Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
by: Hwang, Youngsik, et al.
Published: (2024)

A Priori Error Estimation of Physics-Informed Neural Networks Solving Allen--Cahn and Cahn--Hilliard Equations
by: Zhang, Guangtao, et al.
Published: (2024)

Derivative-free optimization is competitive for aerodynamic design optimization in moderate dimensions
by: Plaban, Punya, et al.
Published: (2025)

Cayley Commutator-free Methods for Krotov-Type Algorithms in Quantum Optimal Control
by: Wembe, Boris, et al.
Published: (2026)

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
by: Peng, Liangzu, et al.
Published: (2024)

Separation-free exponential fitting with structured noise, with applications to inverse problems in parabolic PDEs
by: Katz, Rami, et al.
Published: (2025)

Distributionally Robust Shape and Topology Optimization
by: Dapogny, Charles, et al.
Published: (2025)

Accelerated Primal-Dual Proximal Gradient Splitting Methods for Convex-Concave Saddle-Point Problems
by: Luo, Hao
Published: (2024)

Adaptive projected SOR algorithms for nonnegative quadratic programming
by: Miyatake, Yuto, et al.
Published: (2021)

An Adaptive Phase-Field Method for Structural Topology Optimization
by: Jin, Bangti, et al.
Published: (2023)

On the global complexity of a derivative-free Levenberg-Marquardt algorithm via orthogonal spherical smoothing
by: Chen, Xi, et al.
Published: (2024)

Computing cone-constrained singular values of matrices
by: Barbarino, Giovanni, et al.
Published: (2025)

A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
by: Liu, Shu, et al.
Published: (2024)

MAGPIE: Multilevel-Adaptive-Guided Solver for Ptychographic Phase Retrieval
by: Zhang, Borong, et al.
Published: (2025)

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026)

Estimation of the input-to-state stability gain functions from finite-dimensional approximations
by: Hillebrecht, Birgit, et al.
Published: (2026)

The Mean Value Theorem: Analytical Proof and Computational Approaches
by: Barboza, Márcio Matheus de Lima, et al.
Published: (2025)

R-Adaptive Mesh Optimization to Enhance Finite Element Basis Compression
by: Harper, Graham, et al.
Published: (2024)

Identification of Feasible Regions Using R-Functions
by: Kucherenko, Segei, et al.
Published: (2025)

Computing AD-compatible subgradients of convex relaxations of implicit functions
by: Song, Yingkai, et al.
Published: (2025)

Iterative Proximal-Minimization for Computing Saddle Points with Fixed Index
by: Gu, Shuting, et al.
Published: (2025)

Stochastic Zeroth-Order Method for Computing Generalized Rayleigh Quotients
by: Bresch, Jonas, et al.
Published: (2025)

Adaptive Approximations of Inclusions in a Semilinear Elliptic Problem Related to Cardiac Electrophysiology
by: Jin, Bangti, et al.
Published: (2025)

Computational Control of Nonlinear Partial Differential Equations Using Machine Learning
by: Kurbanov, Maximilian, et al.
Published: (2026)

Computation and Control of Unstable Steady States for Mean Field Multiagent Systems
by: Bicego, Sara, et al.
Published: (2024)