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Regression

4964 directly classified papers

Papers per year

Papers

On kernel-based statistical learning theory in the mean field limit NIPS 2023
No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling NIPS 2023
Shapley Based Residual Decomposition for Instance Analysis ICML 2023
Constrained Monotonic Neural Networks ICML 2023
Distributional Offline Policy Evaluation with Predictive Error Guarantees ICML 2023
Distance Weighted Supervised Learning for Offline Interaction Data ICML 2023
Stochastic Gradient Descent under Markovian Sampling Schemes ICML 2023
Agnostically Learning Single-Index Models using Omnipredictors NIPS 2023
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models NIPS 2023
Learning the Efficient Frontier NIPS 2023
Group SLOPE Penalized Low-Rank Tensor Regression JMLR 2023
Modular Regression: Improving Linear Models by Incorporating Auxiliary Data JMLR 2023
Dimensionality Reduction and Wasserstein Stability for Kernel Regression JMLR 2023
Benign Overfitting of Constant-Stepsize SGD for Linear Regression JMLR 2023
On the Identifiability and Estimation of Causal Location-Scale Noise Models ICML 2023
Mixed Regression via Approximate Message Passing JMLR 2023
Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression JMLR 2023
Demographic Parity Constrained Minimax Optimal Regression under Linear Model NIPS 2023
Dimension Reduction and MARS JMLR 2023
Fast Screening Rules for Optimal Design via Quadratic Lasso Reformulation JMLR 2023
High-Dimensional Inference for Generalized Linear Models with Hidden Confounding JMLR 2023
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty JMLR 2023
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective ICML 2023
Elastic Gradient Descent, an Iterative Optimization Method Approximating the Solution Paths of the Elastic Net JMLR 2023
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023