Cover Image

Scalable and adaptive prediction bands with kernel sum-of-squares

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Allain, Louis, da Veiga, Sébastien, Staber, Brian
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Asymmetric conformal prediction with penalized kernel sum-of-squares
by: Allain, Louis, et al.
Published: (2026)

Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels
by: Perez, Raphaël Carpintero, et al.
Published: (2024)

Improved learning theory for kernel distribution regression with two-stage sampling
by: Bachoc, François, et al.
Published: (2023)

Physics-informed kernel learning
by: Doumèche, Nathan, et al.
Published: (2024)

The phase diagram of kernel interpolation in large dimensions
by: Zhang, Haobo, et al.
Published: (2024)

On the number of modes of Gaussian kernel density estimators
by: Geshkovski, Borjan, et al.
Published: (2024)

Local versions of sum-of-norms clustering
by: Dunlap, Alexander, et al.
Published: (2021)

Early stopping and polynomial smoothing in regression with reproducing kernels
by: Averyanov, Yaroslav, et al.
Published: (2020)

Gradient dynamics for low-rank fine-tuning beyond kernels
by: Dayi, Arif Kerem, et al.
Published: (2024)

Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
by: De Castro, Yohann, et al.
Published: (2025)

Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
by: Haas, Moritz, et al.
Published: (2023)

Consistent estimation of generative model representations in the data kernel perspective space
by: Acharyya, Aranyak, et al.
Published: (2024)

Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
by: Cheng, Xiuyuan, et al.
Published: (2021)

Learning signals defined on graphs with optimal transport and Gaussian process regression
by: Perez, Raphaël Carpintero, et al.
Published: (2024)

To bootstrap or to rollout? An optimal and adaptive interpolation
by: Mou, Wenlong, et al.
Published: (2024)

Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models
by: Zhu, Libin, et al.
Published: (2026)

Fast kernel methods: Sobolev, physics-informed, and additive models
by: Doumèche, Nathan, et al.
Published: (2025)

Statistical Inference for Linear Functionals of Online Least-squares SGD when $t \gtrsim d^{1+δ}$
by: Agrawalla, Bhavya, et al.
Published: (2025)

Minimax-optimal and Locally-adaptive Online Nonparametric Regression
by: Liautaud, Paul, et al.
Published: (2024)

Reflected diffusion models adapt to low-dimensional data
by: Holk, Asbjørn, et al.
Published: (2026)

When few labeled target data suffice: a theory of semi-supervised domain adaptation via fine-tuning from multiple adaptive starts
by: Ha, Wooseok, et al.
Published: (2025)

The loss landscape of deep linear neural networks: a second-order analysis
by: Achour, El Mehdi, et al.
Published: (2021)

An adaptive transfer learning perspective on classification in non-stationary environments
by: Reeve, Henry W J
Published: (2024)

Examining marginal properness in the external validation of survival models with squared and logarithmic losses
by: Sonabend, Raphael, et al.
Published: (2022)

Wild refitting for black box prediction
by: Wainwright, Martin J.
Published: (2025)

Approximate full conformal prediction in an RKHS
by: Razafindrakoto, Davidson Lova, et al.
Published: (2026)

Online selective conformal inference: adaptive scores, convergence rate and optimality
by: Humbert, Pierre, et al.
Published: (2025)

Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
by: Bellec, Pierre C, et al.
Published: (2021)

Multi-modal contrastive learning adapts to intrinsic dimensions of shared latent variables
by: Gui, Yu, et al.
Published: (2025)

Scalable multitask Gaussian processes for complex mechanical systems with functional covariates
by: Gninkou, Razak Christophe Sabi, et al.
Published: (2026)

Thompson sampling: Precise arm-pull dynamics and adaptive inference
by: Han, Qiyang
Published: (2026)

Universal distribution of the empirical coverage in split conformal prediction
by: F, Paulo C. Marques
Published: (2023)

A review of predictive uncertainty estimation with machine learning
by: Tyralis, Hristos, et al.
Published: (2022)

Iteratively reweighted kernel machines efficiently learn sparse functions
by: Zhu, Libin, et al.
Published: (2025)

Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
by: Zhang, Shuofeng, et al.
Published: (2025)

UCB algorithms for multi-armed bandits: Precise regret and adaptive inference
by: Han, Qiyang, et al.
Published: (2024)

Marginal and training-conditional guarantees in one-shot federated conformal prediction
by: Humbert, Pierre, et al.
Published: (2024)

A sparse PAC-Bayesian approach for high-dimensional quantile prediction
by: Mai, The Tien
Published: (2024)

Selecting informative conformal prediction sets with false coverage rate control
by: Gazin, Ulysse, et al.
Published: (2024)

A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces
by: Wynne, George, et al.
Published: (2022)