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Regression

5,004 papers

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Papers

SPDE-Net: Neural Network based prediction of stabilization parameter for SUPG technique ACML 2021
CTS2: Time Series Smoothing with Constrained Reinforcement Learning ACML 2021
Robust Regression for Monocular Depth Estimation ACML 2021
LassoNet: Neural Networks with Feature Sparsity AISTATS 2021
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series AISTATS 2021
Online Forgetting Process for Linear Regression Models AISTATS 2021
Nonlinear Functional Output Regression: A Dictionary Approach AISTATS 2021
Online Sparse Reinforcement Learning AISTATS 2021
Adversarially Robust Estimate and Risk Analysis in Linear Regression AISTATS 2021
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications AISTATS 2021
Kernel regression in high dimensions: Refined analysis beyond double descent AISTATS 2021
Learning Prediction Intervals for Regression: Generalization and Calibration AISTATS 2021
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation AISTATS 2021
Parametric Programming Approach for More Powerful and General Lasso Selective Inference AISTATS 2021
Hadamard Wirtinger Flow for Sparse Phase Retrieval AISTATS 2021
Gaming Helps! Learning from Strategic Interactions in Natural Dynamics AISTATS 2021
Tractable contextual bandits beyond realizability AISTATS 2021
Efficient Statistics for Sparse Graphical Models from Truncated Samples AISTATS 2021
Stability and Risk Bounds of Iterative Hard Thresholding AISTATS 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms AISTATS 2021
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations AISTATS 2021
Gradient Descent in RKHS with Importance Labeling AISTATS 2021
Localizing Changes in High-Dimensional Regression Models AISTATS 2021
Stochastic Gradient Descent Meets Distribution Regression AISTATS 2021
The Sample Complexity of Meta Sparse Regression AISTATS 2021