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Regression

4,964 papers

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Papers

Sparse Learning with CART NIPS 2020
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery NIPS 2020
Matérn Gaussian Processes on Riemannian Manifolds NIPS 2020
How many samples is a good initial point worth in Low-rank Matrix Recovery? NIPS 2020
Efficient estimation of neural tuning during naturalistic behavior NIPS 2020
Non-parametric Models for Non-negative Functions NIPS 2020
Autofocused oracles for model-based design NIPS 2020
Debiasing Averaged Stochastic Gradient Descent to handle missing values NIPS 2020
Sample complexity and effective dimension for regression on manifolds NIPS 2020
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions NIPS 2020
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent NIPS 2020
Spike and slab variational Bayes for high dimensional logistic regression NIPS 2020
The Strong Screening Rule for SLOPE NIPS 2020
Deep Evidential Regression NIPS 2020
Distributionally Robust Local Non-parametric Conditional Estimation NIPS 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
Non-Crossing Quantile Regression for Distributional Reinforcement Learning NIPS 2020
Cross-validation Confidence Intervals for Test Error NIPS 2020
Gaussian Gated Linear Networks NIPS 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization NIPS 2020
Calibrated Reliable Regression using Maximum Mean Discrepancy NIPS 2020
A convex optimization formulation for multivariate regression NIPS 2020
X-CAL: Explicit Calibration for Survival Analysis NIPS 2020
Tensor Completion Made Practical NIPS 2020