Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
Fuente:
arXiv
Saved in:
| Main Authors: | Shi, Zhaoyang, Balasubramanian, Krishnakumar, Polonik, Wolfgang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
by: Jin, Yanhao, et al.
Published: (2024)
by: Jin, Yanhao, et al.
Published: (2024)
Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
by: Balasubramanian, Krishnakumar
Published: (2026)
by: Balasubramanian, Krishnakumar
Published: (2026)
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024)
by: Liang, Haodong, et al.
Published: (2024)
Kernel smoothing on manifolds
by: Bae, Eunseong, et al.
Published: (2026)
by: Bae, Eunseong, et al.
Published: (2026)
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
by: Agrawalla, Bhavya, et al.
Published: (2023)
by: Agrawalla, Bhavya, et al.
Published: (2023)
Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)
Algorithms for ridge estimation with convergence guarantees
by: Qiao, Wanli, et al.
Published: (2021)
by: Qiao, Wanli, et al.
Published: (2021)
Dense associative memory for Gaussian distributions
by: Tankala, Chandan, et al.
Published: (2025)
by: Tankala, Chandan, et al.
Published: (2025)
Riemannian Proximal Sampler for High-accuracy Sampling on Manifolds
by: Guan, Yunrui, et al.
Published: (2025)
by: Guan, Yunrui, 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)
by: Agrawalla, Bhavya, et al.
Published: (2025)
Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
by: Liang, Haodong, et al.
Published: (2025)
by: Liang, Haodong, et al.
Published: (2025)
Optimal Demixing of Nonparametric Densities
by: Fan, Jianqing, et al.
Published: (2026)
by: Fan, Jianqing, et al.
Published: (2026)
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
by: Banerjee, Sayan, et al.
Published: (2024)
by: Banerjee, Sayan, et al.
Published: (2024)
A Quantitative Characterization of Forgetting in Post-Training
by: Balasubramanian, Krishnakumar, et al.
Published: (2026)
by: Balasubramanian, Krishnakumar, et al.
Published: (2026)
Gaussian random field approximation via Stein's method with applications to wide random neural networks
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
Finite-Particle Rates for Regularized Stein Variational Gradient Descent
by: He, Ye, et al.
Published: (2026)
by: He, Ye, et al.
Published: (2026)
Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets
by: Landa, Boris, et al.
Published: (2024)
by: Landa, Boris, et al.
Published: (2024)
Total Variation Rates for Riemannian Flow Matching
by: Guan, Yunrui, et al.
Published: (2026)
by: Guan, Yunrui, et al.
Published: (2026)
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
by: He, Ye, et al.
Published: (2024)
by: He, Ye, et al.
Published: (2024)
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
Nonparametric Instrumental Variable Regression with Observed Covariates
by: Shen, Zikai, et al.
Published: (2025)
by: Shen, Zikai, et al.
Published: (2025)
Online Quantile Regression for Nonparametric Additive Models
by: Zhan, Haoran
Published: (2026)
by: Zhan, Haoran
Published: (2026)
Nested Nonparametric Instrumental Variable Regression
by: Meza, Isaac, et al.
Published: (2021)
by: Meza, Isaac, et al.
Published: (2021)
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
by: Liautaud, Paul, et al.
Published: (2024)
by: Liautaud, Paul, et al.
Published: (2024)
A kernel-based analysis of Laplacian Eigenmaps
by: Wahl, Martin
Published: (2024)
by: Wahl, Martin
Published: (2024)
Minimax Adaptive Online Nonparametric Regression over Besov Spaces
by: Liautaud, Paul, et al.
Published: (2025)
by: Liautaud, Paul, et al.
Published: (2025)
Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Asymptotic expansions for spectral convergence of compact self-adjoint operators on general spectral subsets, with application to kernel Gram matrices
by: Bae, Eunseong, et al.
Published: (2026)
by: Bae, Eunseong, et al.
Published: (2026)
Nonparametric Estimation of Joint Entropy via Partitioned Sample-Spacing
by: Ho, Jungwoo, et al.
Published: (2025)
by: Ho, Jungwoo, et al.
Published: (2025)
Sharp Generalization for Nonparametric Regression in Interpolation Space by Over-Parameterized Neural Networks Trained with Preconditioned Gradient Descent and Early Stopping
by: Yang, Yingzhen, et al.
Published: (2024)
by: Yang, Yingzhen, et al.
Published: (2024)
Regularized Stein Variational Gradient Flow
by: He, Ye, et al.
Published: (2022)
by: He, Ye, et al.
Published: (2022)
Batched Nonparametric Contextual Bandits
by: Jiang, Rong, et al.
Published: (2024)
by: Jiang, Rong, et al.
Published: (2024)
Nonparametric Factor Analysis and Beyond
by: Zheng, Yujia, et al.
Published: (2025)
by: Zheng, Yujia, et al.
Published: (2025)
Nonparametric logistic regression with deep learning
by: Yara, Atsutomo, et al.
Published: (2024)
by: Yara, Atsutomo, et al.
Published: (2024)
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise
by: Cheng, Xiuyuan, et al.
Published: (2022)
by: Cheng, Xiuyuan, et al.
Published: (2022)
Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers
by: Ching, Michelle, et al.
Published: (2026)
by: Ching, Michelle, et al.
Published: (2026)
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood
by: Aragam, Bryon, et al.
Published: (2024)
by: Aragam, Bryon, et al.
Published: (2024)
SPDE Methods for Nonparametric Bayesian Posterior Contraction and Laplace Approximation
by: Alberola-Boloix, Enric, et al.
Published: (2026)
by: Alberola-Boloix, Enric, et al.
Published: (2026)
Similar Items
-
Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
by: Shi, Zhaoyang, et al.
Published: (2024) -
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024) -
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
by: Jin, Yanhao, et al.
Published: (2024) -
Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
by: Balasubramanian, Krishnakumar
Published: (2026) -
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024)