Results 101 to 110 of about 12,640,042 (291)
MathematicsSupport vector regression (SVR) is a well-established kernel-based method for nonlinear regression. However, standard SVR formulations minimize absolute-error losses, which are not consistent with the scale-free, relative-accuracy criteria prevalent in ...
Pablo Benavides-Herrera +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.An organic neuromorphic architecture for the classification of human motor behavior is presented and validated. It performs somatic integration by linearly combining the activity from three muscles. An investigation of synaptic weights is presented and discussed in relationship with the classification performance.
Ilenia Sergi +7 more
wiley +1 more source
Consistency and robustness of kernel based regression [PDF]
We investigate properties of kernel based regression (KBR) methods which are inspired by the convex risk minimization method of support vector machines.
Christmann, Andreas, Steinwart, Ingo
core
From Kernel Matrices to Kernel Functions: An Eigenfunction-Based Approach
MathematicsKernel-combination procedures used in classification often return only a combined kernel matrix on the training sample, rather than a kernel function that can be evaluated consistently at new points. This limitation is especially important for supervised
Alberto Muñoz +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye +8 more
wiley +1 more source
MetrologyA robust evaluation of predictive uncertainty is essential for deploying machine learning models in high-risk sectors. While various techniques such as Gaussian Processes and Bayesian Neural Networks have been considered to address model uncertainty, the
Alberto Bottacin, Francesca R. Pennecchi
doaj +1 more source
Quantum machine learning beyond kernel methods. [PDF]
Nat Commun, 2023 Jerbi S +5 more
europepmc +1 more source
XTRUDE: A Process‐Informed Framework for High‐Fidelity Analysis of Hydrogel Extrusion
Advanced Functional Materials, EarlyView.Extrusion performance emerges from the interplay between material properties and processing conditions. XTRUDE (eXTrusion Rheology for Understanding and Defining Extrudability) recreates the extrusion environment with in situ pressure and temperature sensing, enabling characteristic pressure signatures to quantify extrusion‐specific phenomena and ...
Farhad Sanaei +4 more
wiley +1 more source
Feature selection for kernel methods in systems biology. [PDF]
NAR Genom Bioinform, 2022 Brouard C +3 more
europepmc +1 more source
Intracrystalline Void‐Mediated Toughening of Brittle Crystals in Quail Eggshells
Advanced Functional Materials, EarlyView.In quail eggshells, the high density and disordered arrangement of intracrystalline voids inhibit lattice cleavage, suppress long‐range crack propagation, and promote deformation twinning and quasi‐plasticity, serving as an essential toughening motif. We show that these voids remain within a narrow subcritical size range and therefore predominantly do ...
Jingxiao Zhong +16 more
wiley +1 more source