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20232026
most citedOn the convergence of generalized kernel-based interpolation by greedy data selection algorithms

1 citations · 1 across the 8 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.LG2024

Learning phase-space flows using time-discrete implicit Runge-Kutta PINNs

Álvaro Fernández Corral, Nicolás Mendoza, Armin Iske +2

We present a computational framework for obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations, using high-order implicit Runge-K…

stat.ML2024

Bounds on the Generalization Error in Active Learning

Vincent Menden, Yahya Saleh, Armin Iske

We establish empirical risk minimization principles for active learning by deriving a family of upper bounds on the generalization error. Aligning with empirical observations, the…

math.NA2024

Spectral alignment of kernel matrices and applications

Tizan Wenzel, Armin Iske

Kernel matrices are a key quantity in kernel-based approximation, and important properties such as stability and algorithmic convergence can be analyzed with their help. In this wo…

math.NA2024★ 1 cited

On the convergence of generalized kernel-based interpolation by greedy data selection algorithms

Kristof Albrecht, Armin Iske

We analyze the convergence of generalized kernel-based interpolation methods. This is done under minimalistic assumptions on both the kernel and the target function. On these groun…

math.FA2024

Inducing Riesz and orthonormal bases in via composition operators

Yahya Saleh, Armin Iske

Let be a composition operator mapping into for some open sets . We characterize the mappings that transform Riesz b…

cs.LG2024

Finetuning greedy kernel models by exchange algorithms

Tizian Wenzel, Armin Iske

Kernel based approximation offers versatile tools for high-dimensional approximation, which can especially be leveraged for surrogate modeling. For this purpose, both "knot inserti…