generalization bound

Towards Sharper Generalization Bounds for Adversarial Contrastive Learning IJCAI 2024 Towards Sharper Risk Bounds for Minimax Problems IJCAI 2024 Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024 Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens NeurIPS 2024 Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features ICML 2024 Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States UAI 2024 Understanding Domain Generalization: A Noise Robustness Perspective ICLR 2024 Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters AISTATS 2024 Understanding prompt engineering may not require rethinking generalization ICLR 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling UAI 2024 Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024 Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models NeurIPS 2024 Weighted distance nearest neighbor condensing ICML 2024 L_2-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting NeurIPS 2023 Adversarial Self-Training Improves Robustness and Generalization for Gradual Domain Adaptation NeurIPS 2023 Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks AAAI 2023 A graphon-signal analysis of graph neural networks NeurIPS 2023 Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation AISTATS 2023 Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions ICML 2023 Analyzing Generalization of Neural Networks through Loss Path Kernels NeurIPS 2023 An Information Theory Perspective on Variance-Invariance-Covariance Regularization NeurIPS 2023 Approximation-Generalization Trade-offs under (Approximate) Group Equivariance NeurIPS 2023 A Theory of Multimodal Learning NeurIPS 2023 A unified framework for information-theoretic generalization bounds NeurIPS 2023 A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning NeurIPS 2023