conftrace_
← Core Methods
Machine Learning › Core Methods ›

Regression

4,964 papers

Papers per year

Papers

Posterior Contraction for Deep Gaussian Process Priors JMLR 2023
Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data JMLR 2023
Approximate Post-Selective Inference for Regression with the Group LASSO JMLR 2023
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023
Gaussian Processes with Errors in Variables: Theory and Computation JMLR 2023
Statistical Inference for Noisy Incomplete Binary Matrix JMLR 2023
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023
The Implicit Bias of Benign Overfitting JMLR 2023
An Annotated Graph Model with Differential Degree Heterogeneity for Directed Networks JMLR 2023
Benign overfitting in ridge regression JMLR 2023
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data JMLR 2023
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators JMLR 2023
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks JMLR 2023
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments JMLR 2023
Integrating Random Effects in Deep Neural Networks JMLR 2023
Flexible Model Aggregation for Quantile Regression JMLR 2023
A Framework and Benchmark for Deep Batch Active Learning for Regression JMLR 2023
Robust Methods for High-Dimensional Linear Learning JMLR 2023
Inference on the Change Point under a High Dimensional Covariance Shift JMLR 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points JMLR 2023
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization JMLR 2023
Least Squares Model Averaging for Distributed Data JMLR 2023
Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data JMLR 2023