excess risk

Generalization in Kernel Regression Under Realistic Assumptions ICML 2024 Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples ICML 2024 Multiple Descent in the Multiple Random Feature Model JMLR 2024 On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Models JMLR 2024 On Convex Optimization with Semi-Sensitive Features COLT 2024 On the Efficiency of ERM in Feature Learning NeurIPS 2024 Private Geometric Median NeurIPS 2024 Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses ICML 2024 Quasi-Monte Carlo Features for Kernel Approximation ICML 2024 Robust Multi-Task Learning with Excess Risks ICML 2024 Smoothness Adaptive Hypothesis Transfer Learning ICML 2024 The optimality of kernel classifiers in Sobolev space ICLR 2024 Understanding the Gains from Repeated Self-Distillation NeurIPS 2024 Benign Overfitting of Constant-Stepsize SGD for Linear Regression JMLR 2023 Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD ICLR 2023 Deep linear networks can benignly overfit when shallow ones do JMLR 2023 Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods ICLR 2023 Exploring Local Norms in Exp-concave Statistical Learning COLT 2023 Exponential Generalization Bounds with Near-Optimal Rates for L_q-Stable Algorithms ICLR 2023 Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron ICML 2023 On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay NeurIPS 2023 On the Size and Approximation Error of Distilled Datasets NeurIPS 2023 Optimistic Rates for Multi-Task Representation Learning NeurIPS 2023 Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses ALT 2023 Sequential Counterfactual Risk Minimization ICML 2023