Gaussian kernel expansion with basis functions uniformly bounded in $\mathcal{L}_{\infty}$
Fuente:
arXiv
Saved in:
| Main Authors: | Bisiacco, Mauro, Pillonetto, Gianluigi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning stochasticity: a nonparametric framework for intrinsic noise estimation
by: Pillonetto, Gianluigi, et al.
Published: (2025)
by: Pillonetto, Gianluigi, et al.
Published: (2025)
Sparse and nonparametric estimation of equations governing dynamical systems with applications to biology
by: Pillonetto, G., et al.
Published: (2025)
by: Pillonetto, G., et al.
Published: (2025)
On-line learning of dynamic systems: sparse regression meets Kalman filtering
by: Pillonetto, Gianluigi, et al.
Published: (2025)
by: Pillonetto, Gianluigi, et al.
Published: (2025)
Lipschitz bounds for integral kernels
by: Reverdi, Justin, et al.
Published: (2026)
by: Reverdi, Justin, et al.
Published: (2026)
Regularized System Identification
by: Pillonetto, Gianluigi, et al.
Published: (2022)
by: Pillonetto, Gianluigi, et al.
Published: (2022)
Neurally-plausible radial basis kernels using distributed Fourier embeddings
by: Chouinard, Jakeb
Published: (2026)
by: Chouinard, Jakeb
Published: (2026)
Uniform convergence for Gaussian kernel ridge regression
by: Dommel, Paul, et al.
Published: (2025)
by: Dommel, Paul, et al.
Published: (2025)
Concentration bounds for intrinsic dimension estimation using Gaussian kernels
by: Andersson, Martin
Published: (2025)
by: Andersson, Martin
Published: (2025)
A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based nested kernels
by: Perez, Raphaël Carpintero, et al.
Published: (2025)
by: Perez, Raphaël Carpintero, et al.
Published: (2025)
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions
by: Viset, Frida Marie, et al.
Published: (2022)
by: Viset, Frida Marie, et al.
Published: (2022)
Learning functions, operators and dynamical systems with kernels
by: Rosasco, Lorenzo
Published: (2025)
by: Rosasco, Lorenzo
Published: (2025)
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions
by: Tondo, Gledson Rodrigo, et al.
Published: (2025)
by: Tondo, Gledson Rodrigo, et al.
Published: (2025)
On the number of modes of Gaussian kernel density estimators
by: Geshkovski, Borjan, et al.
Published: (2024)
by: Geshkovski, Borjan, et al.
Published: (2024)
Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function
by: Lahr, Amon, et al.
Published: (2026)
by: Lahr, Amon, et al.
Published: (2026)
Nonlinear functional regression by functional deep neural network with kernel embedding
by: Shi, Zhongjie, et al.
Published: (2024)
by: Shi, Zhongjie, et al.
Published: (2024)
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels
by: Perez, Raphaël Carpintero, et al.
Published: (2024)
by: Perez, Raphaël Carpintero, et al.
Published: (2024)
On the generalization of Tanimoto-type kernels to real valued functions
by: Szedmak, Sandor, et al.
Published: (2020)
by: Szedmak, Sandor, et al.
Published: (2020)
A mixed-categorical correlation kernel for Gaussian process
by: Saves, P., et al.
Published: (2022)
by: Saves, P., et al.
Published: (2022)
Instance-dependent uniform tail bounds for empirical processes
by: Bahmani, Sohail
Published: (2022)
by: Bahmani, Sohail
Published: (2022)
CoVAE: Consistency Training of Variational Autoencoders
by: Silvestri, Gianluigi, et al.
Published: (2025)
by: Silvestri, Gianluigi, et al.
Published: (2025)
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
by: Cheng, Xiuyuan, et al.
Published: (2021)
by: Cheng, Xiuyuan, et al.
Published: (2021)
Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
by: Kouw, Wouter M.
Published: (2025)
by: Kouw, Wouter M.
Published: (2025)
DTI-GP: Bayesian operations for drug-target interactions using deep kernel Gaussian processes
by: Bolgár, Bence, et al.
Published: (2025)
by: Bolgár, Bence, et al.
Published: (2025)
Max-sliced Wasserstein concentration and uniform ratio bounds of empirical measures on RKHS
by: Han, Ruiyu, et al.
Published: (2024)
by: Han, Ruiyu, et al.
Published: (2024)
Entrywise error bounds for low-rank approximations of kernel matrices
by: Modell, Alexander
Published: (2024)
by: Modell, Alexander
Published: (2024)
Rectified Gaussian kernel multi-view k-means clustering
by: Sinaga, Kristina P.
Published: (2024)
by: Sinaga, Kristina P.
Published: (2024)
A unified recipe for deriving (time-uniform) PAC-Bayes bounds
by: Chugg, Ben, et al.
Published: (2023)
by: Chugg, Ben, et al.
Published: (2023)
Learning from Partial Chain-of-Thought via Truncated-Reasoning Self-Distillation
by: Silvestri, Gianluigi, et al.
Published: (2026)
by: Silvestri, Gianluigi, et al.
Published: (2026)
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
by: Risser, Mark D., et al.
Published: (2024)
by: Risser, Mark D., et al.
Published: (2024)
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions
by: Aghaei, Alireza Afzal
Published: (2024)
by: Aghaei, Alireza Afzal
Published: (2024)
Achieving the Kesten-Stigum bound in the non-uniform hypergraph stochastic block model
by: Fernandez V, Manuel, et al.
Published: (2026)
by: Fernandez V, Manuel, et al.
Published: (2026)
Model-agnostic basis functions for the 2-point correlation function of dark matter in linear theory
by: Paranjape, Aseem, et al.
Published: (2024)
by: Paranjape, Aseem, et al.
Published: (2024)
Optimal kernel regression bounds under energy-bounded noise
by: Lahr, Amon, et al.
Published: (2025)
by: Lahr, Amon, et al.
Published: (2025)
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
by: Kim, Bongseok, et al.
Published: (2025)
by: Kim, Bongseok, et al.
Published: (2025)
Infinite Neural Operators: Gaussian processes on functions
by: de Souza, Daniel Augusto, et al.
Published: (2025)
by: de Souza, Daniel Augusto, et al.
Published: (2025)
On the similarity of bandwidth-tuned quantum kernels and classical kernels
by: Flórez-Ablan, Roberto, et al.
Published: (2025)
by: Flórez-Ablan, Roberto, et al.
Published: (2025)
Reservoir kernels and Volterra series
by: Gonon, Lukas, et al.
Published: (2022)
by: Gonon, Lukas, et al.
Published: (2022)
On the Pinsker bound of inner product kernel regression in large dimensions
by: Lu, Weihao, et al.
Published: (2024)
by: Lu, Weihao, et al.
Published: (2024)
Iteratively reweighted kernel machines efficiently learn sparse functions
by: Zhu, Libin, et al.
Published: (2025)
by: Zhu, Libin, et al.
Published: (2025)
SchoenbAt: Rethinking Attention with Polynomial basis
by: Guo, Yuhan, et al.
Published: (2025)
by: Guo, Yuhan, et al.
Published: (2025)
Similar Items
-
Learning stochasticity: a nonparametric framework for intrinsic noise estimation
by: Pillonetto, Gianluigi, et al.
Published: (2025) -
Sparse and nonparametric estimation of equations governing dynamical systems with applications to biology
by: Pillonetto, G., et al.
Published: (2025) -
On-line learning of dynamic systems: sparse regression meets Kalman filtering
by: Pillonetto, Gianluigi, et al.
Published: (2025) -
Lipschitz bounds for integral kernels
by: Reverdi, Justin, et al.
Published: (2026) -
Regularized System Identification
by: Pillonetto, Gianluigi, et al.
Published: (2022)