generalization bound

Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses ICLR 2023 Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings AAAI 2023 Generalization bounds for neural ordinary differential equations and deep residual networks NeurIPS 2023 Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels JMLR 2023 Generalization Bounds using Data-Dependent Fractal Dimensions ICML 2023 Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023 Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023 Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization CVPR 2023 GradPU: Positive-Unlabeled Learning via Gradient Penalty and Positive Upweighting AAAI 2023 Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation AISTATS 2023 How much does Initialization Affect Generalization? ICML 2023 Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability ICML 2023 Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation AISTATS 2023 Information Theoretic Lower Bounds for Information Theoretic Upper Bounds NeurIPS 2023 Instance-Dependent Generalization Bounds via Optimal Transport JMLR 2023 Interpolating Classifiers Make Few Mistakes JMLR 2023 Intractability of Learning the Discrete Logarithm with Gradient-Based Methods ACML 2023 Label Distribution Changing Learning with Sample Space Expanding JMLR 2023 Learning a 1-layer conditional generative model in total variation NeurIPS 2023 Learning Curves for Deep Structured Gaussian Feature Models NeurIPS 2023 Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks ICML 2023 Learning Trajectories are Generalization Indicators NeurIPS 2023 Learning via Wasserstein-Based High Probability Generalisation Bounds NeurIPS 2023 MADG: Margin-based Adversarial Learning for Domain Generalization NeurIPS 2023 Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence ICLR 2023