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statistical learning theory

82 papers

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statistical learning (350) support vector machine (976) generalization bound (649) empirical risk minimization (348) learning theory (518) kernel methods (1096) generalization error (285) rademacher complexity (108) learning rate (192) reproducing kernel hilbert space (334)

Papers

Differentially Private Assouad, Fano, and Le Cam ALT 2021
On Optimal Interpolation in Linear Regression NIPS 2021
A Precise Performance Analysis of Support Vector Regression ICML 2021
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning ICML 2021
Failures of Model-dependent Generalization Bounds for Least-norm Interpolation JMLR 2021
Adaptive estimation of nonparametric functionals JMLR 2021
Good Classifiers are Abundant in the Interpolating Regime AISTATS 2021
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation AISTATS 2021
Estimating weighted areas under the ROC curve NIPS 2020
Risk Bounds for Reservoir Computing JMLR 2020
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines ICML 2020
Sharp Asymptotics and Optimal Performance for Inference in Binary Models AISTATS 2020
Towards Problem-dependent Optimal Learning Rates NIPS 2020
Minimax Estimation of Conditional Moment Models NIPS 2020
Toward the Fundamental Limits of Imitation Learning NIPS 2020
Learning from Weakly Dependent Data under Dobrushin’s Condition COLT 2019
On Kernel Derivative Approximation with Random Fourier Features AISTATS 2019
Sharp Analysis of Learning with Discrete Losses AISTATS 2019
Robust Learning from Untrusted Sources ICML 2019
Statistical-Computational Tradeoff in Single Index Models NIPS 2019
Learning to Screen NIPS 2019
Localized Structured Prediction NIPS 2019
Inference in Sparse Graphs with Pairwise Measurements and Side Information AISTATS 2018
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation AISTATS 2017
Minimax Estimation of Kernel Mean Embeddings JMLR 2017