conftrace_

nonparametric regression

111 papers

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Co-occurring keywords

kernel methods (1097) gaussian process (1200) additive model (48) convergence rate (607) variable selection (146) kernel regression (87) bayesian inference (1907) regret bound (1926) minimax rate (87) derivative estimation (10)

Papers

Hierarchical and Stochastic Crystallization Learning: Geometrically Leveraged Nonparametric Regression with Delaunay Triangulation JMLR 2025
Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds JMLR 2025
Random Forest Weighted Local Fréchet Regression with Random Objects JMLR 2024
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes NIPS 2024
Nonparametric Regression for 3D Point Cloud Learning JMLR 2024
Robust Nonparametric Regression under Poisoning Attack AAAI 2024
Efficient Agnostic Learning with Average Smoothness ALT 2024
Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks JMLR 2024
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients NIPS 2024
More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization JMLR 2024
Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design JMLR 2024
Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression AISTATS 2024
$\texttt{causalAssembly}$: Generating Realistic Production Data for Benchmarking Causal Discovery CLEAR 2024
Transformers are Minimax Optimal Nonparametric In-Context Learners NIPS 2024
Deep Nonparametric Quantile Regression under Covariate Shift JMLR 2024
Nonparametric Gaussian Process Covariances via Multidimensional Convolutions AISTATS 2023
Dimension Reduction and MARS JMLR 2023
Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data JMLR 2023
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators JMLR 2023
The Art of BART: Minimax Optimality over Nonhomogeneous Smoothness in High Dimension JMLR 2023
Posterior Contraction for Deep Gaussian Process Priors JMLR 2023
Nonparametric Iterative Machine Teaching ICML 2023
Gaussian Processes with Errors in Variables: Theory and Computation JMLR 2023
Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions NIPS 2023