9 citations · 26 across the 13 of their papers we have counts for
5 papers · 1 filter
Interpolation with the polynomial kernels
Giacomo Elefante, Wolfgang Erb, Francesco Marchetti +3
The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are r…
Equally spaced points are optimal for Brownian Bridge kernel interpolation
Gabriele Santin
In this paper we show how ideas from spline theory can be used to construct a local basis for the space of translates of a general iterated Brownian Bridge kernel $k_{β,\varepsilon…
Adaptive meshfree approximation for linear elliptic partial differential equations with PDE-greedy kernel methods
Tizian Wenzel, Daniel Winkle, Gabriele Santin +1
We consider meshless approximation for solutions of boundary value problems (BVPs) of elliptic Partial Differential Equations (PDEs) via symmetric kernel collocation. We discuss th…
Reprogramming FairGANs with Variational Auto-Encoders: A New Transfer Learning Model
Beatrice Nobile, Gabriele Santin, Bruno Lepri +1
Fairness-aware GANs (FairGANs) exploit the mechanisms of Generative Adversarial Networks (GANs) to impose fairness on the generated data, freeing them from both disparate impact an…
Stability of convergence rates: Kernel interpolation on non-Lipschitz domains
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
Error estimates for kernel interpolation in Reproducing Kernel Hilbert Spaces (RKHS) usually assume quite restrictive properties on the shape of the domain, especially in the case…