generalization analysis

A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops ICLR 2025 How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? AAAI 2025 Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons AISTATS 2025 Stability and Generalization for Stochastic (Compositional) Optimizations IJCAI 2025 Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology AAAI 2025 Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis ICLR 2025 Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection ICML 2024 Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms ICML 2024 Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation ICML 2023 On the Capacity Limits of Privileged ERM AISTATS 2023 Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems COLT 2023 The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization AAAI 2023 Generalization Analysis on Learning with a Concurrent Verifier NeurIPS 2022 Provable Learning-based Algorithm For Sparse Recovery ICLR 2022 Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations NeurIPS 2022 Learning with Feature and Distribution Evolvable Streams ICML 2020 Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces NeurIPS 2020 Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks NeurIPS 2020 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010