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A derivative-free scaling memoryless DFP method for solving large scale nonlinear monotone equations
Quasi-Newton methods for solving nonlinear system of equations provide an attractive alternative to the Newton method in which they do not require...
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Modified Memoryless Spectral-Scaling Broyden Family on Riemannian Manifolds
This paper presents modified memoryless quasi-Newton methods based on the spectral-scaling Broyden family on Riemannian manifolds. The method...
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Preconditioning and Scaling
The performance of the scalable algorithms can be improved by the preconditioning and scaling adapted to the structure of the contact problem. The...
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Distributed Optimization and Scaling Design for Solving Sylvester Equations
This paper develops distributed algorithms for solving Sylvester equations. The authors transform solving Sylvester equations into a distributed...
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The Probabilistic Scaling Paradigm
In this note we further discuss the probabilistic scaling introduced by the authors in (ar**v:1910.08492, 2019) and (Invent. Math. 228, 539–686,...
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Generalized scaling for the constrained maximum-entropy sampling problem
The best practical techniques for exact solution of instances of the constrained maximum-entropy sampling problem, a discrete-optimization problem...
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Epidemic modelling by birth-death processes with spatial scaling
In epidemic modeling, interpretation of compartment quantities, such as s , i , and r in relevant equations, is not always straightforward. Ambiguities...
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A Taste of Scaling Limit
In this chapter, we overfly the scaling limit theory for random planar maps.
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Hybrid Kinetic/Fluid Numerical Method for the Vlasov-Poisson-BGK Equation in the Diffusive Scaling
This shortLaidin, Tino noteRey, Thomas presents an extension of the hybrid, model-adaptation method introduced in T. Laidin, ar**v 2202.03696, 2022...
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An efficient partial parallel method with scaling step size strategy for three-block convex optimization problems
A popular optimization model arising from image processing is the separable optimization problem whose objective function is the sum of three...
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Memoryless Quasi-Newton Methods Based on the Spectral-Scaling Broyden Family for Riemannian Optimization
We consider iterative methods for unconstrained optimization on Riemannian manifolds. Though memoryless quasi-Newton methods are effective for...
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On Scaling Laws for Multi-Well Nucleation Problems Without Gauge Invariances
In this article, we study scaling laws for simplified multi-well nucleation problems without gauge invariances which are motivated by models for...
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Hamilton–Jacobi scaling limits of Pareto peeling in 2D
Pareto hull peeling is a discrete algorithm, generalizing convex hull peeling, for sorting points in Euclidean space. We prove that Pareto peeling of...
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Free boundary dimers: random walk representation and scaling limit
We study the dimer model on subgraphs of the square lattice in which vertices on a prescribed part of the boundary (the free boundary) are possibly...
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An Affine Scaling Algorithm for Biobjective Linear Programming
Given a biobjective linear programming problem, we develop an affine scaling algorithm with min-max direction and demonstrate its convergence for an...
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Scaling relations for auxin waves
We analyze an ‘up-the-gradient’ model for the formation of transport channels of the phytohormone auxin, through auxin-mediated polarization of the...
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On a Particular Scaling for the Prototype Anisotropic p-Laplacian
In this brief note we show that under a volume non-preserving scaling it is possible to recover the basics for a regularity theory regarding local...
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Geometric multidimensional scaling: efficient approach for data dimensionality reduction
Multidimensional scaling (MDS) is an often-used method to reduce the dimensionality of multidimensional data nonlinearly and to present the data...
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Scaling Limits of Slim and Fat Trees
We consider Galton–Watson trees conditioned on both the total number of vertices n and the number of leaves k . The focus is on the case in which both k ...
