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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

Statistical Learning Theory for Distributional Classification AAAI 2026
Credal Learning Theory NIPS 2024
Concentration and Moment Inequalities for General Functions of Independent Random Variables with Heavy Tails JMLR 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures AISTATS 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality NIPS 2024
Grokking phase transitions in learning local rules with gradient descent JMLR 2024
An Entropy-Based Model for Hierarchical Learning JMLR 2024
Faster Rates of Differentially Private Stochastic Convex Optimization JMLR 2024
Learning from many trajectories JMLR 2024
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs NIPS 2024
On the Optimality of Misspecified Kernel Ridge Regression ICML 2023
On kernel-based statistical learning theory in the mean field limit NIPS 2023
Optimal Convergence Rates for Distributed Nystroem Approximation JMLR 2023
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron ICML 2023
Revisiting minimum description length complexity in overparameterized models JMLR 2023
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints NIPS 2023
Sampling-based Nyström Approximation and Kernel Quadrature ICML 2023
On the Variance, Admissibility, and Stability of Empirical Risk Minimization NIPS 2023
Strong Gaussian Approximation for the Sum of Random Vectors COLT 2022
Online PAC-Bayes Learning NIPS 2022
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression NIPS 2022
On the Statistical Benefits of Curriculum Learning ICML 2022
Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification JMLR 2022
KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss AAAI 2022