uniform convergence

A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes ALT 2026 Learning with Monotone Adversarial Corruptions ALT 2026 Uniform Convergence Beyond Glivenko-Cantelli ALT 2026 Uniform Laws of Large Numbers in Product Spaces COLT 2026 Do PAC-Learners Learn the Marginal Distribution? ALT 2025 Loss Gradient Gaussian Width based Generalization and Optimization Guarantees AISTATS 2025 Efficient Agnostic Learning with Average Smoothness ALT 2024 Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization AISTATS 2024 List Sample Compression and Uniform Convergence COLT 2024 Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent JMLR 2024 The sample complexity of ERMs in stochastic convex optimization AISTATS 2024 Generalization Bounds for Adversarial Metric Learning IJCAI 2023 Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks NeurIPS 2023 Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence ICLR 2023 Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation ICML 2023 Multiclass Online Learning and Uniform Convergence COLT 2023 Open problem: log(n) factor in "Local Glivenko-Cantelli" COLT 2023 Uniform Convergence with Square-Root Lipschitz Loss NeurIPS 2023 Universal Rates for Multiclass Learning COLT 2023 Generalization Analysis of Message Passing Neural Networks on Large Random Graphs NeurIPS 2022 Integral Probability Metrics PAC-Bayes Bounds NeurIPS 2022 Non-asymptotic and Accurate Learning of Nonlinear Dynamical Systems JMLR 2022 PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency AISTATS 2022 Supervised Learning with General Risk Functionals ICML 2022 The Sample Complexity of One-Hidden-Layer Neural Networks NeurIPS 2022