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math.NA2026
Greedy multiscale kernel algorithms
Sara Avesani, Armin Iske, Michael Multerer +1
Multiscale kernel approximation and greedy kernel algorithms are two established tools for scattered data approximation. We combine them into greedy multiscale kernel algorithms, i…
math.NA2026
Samplet compression for conditionally positive definite kernels and universal Kriging
Sara Avesani, Rüdiger Kempf, Michael Multerer +1
We present a samplet-based framework for the efficient numerical solution of saddle-point systems arising from conditionally positive definite (CPD) kernel approximation in general…
math.NA2026
Tree-Adaptive Multiscale Kernel Lasso in Samplet Coordinates
Sara Avesani, Gaia Fumagalli, Michael Multerer +1
We develop a novel framework for sparse multiscale kernel approximation of large scattered data problems based on a samplet representation. Samplets form a multiresolution analysis…