conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Statistical Learning

4,076 papers

Papers per year

Papers

A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning NIPS 2020
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization NIPS 2020
Minimax Estimation of Conditional Moment Models NIPS 2020
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NIPS 2020
Reliable Graph Neural Networks via Robust Aggregation NIPS 2020
Sample Complexity of Uniform Convergence for Multicalibration NIPS 2020
Efficient Learning of Discrete Graphical Models NIPS 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals NIPS 2020
Learning Bounds for Risk-sensitive Learning 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
Learning the Linear Quadratic Regulator from Nonlinear Observations NIPS 2020
When Do Neural Networks Outperform Kernel Methods? NIPS 2020
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation NIPS 2020
Sharp uniform convergence bounds through empirical centralization NIPS 2020
Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors NIPS 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples NIPS 2020
On Learning Ising Models under Huber's Contamination Model NIPS 2020
Cross-validation Confidence Intervals for Test Error NIPS 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
On the Equivalence between Online and Private Learnability beyond Binary Classification NIPS 2020
PAC-Bayes Analysis Beyond the Usual Bounds NIPS 2020
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class NIPS 2020
A convex optimization formulation for multivariate regression NIPS 2020
Axioms for Learning from Pairwise Comparisons NIPS 2020