generalization bound

A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds JMLR 2023 Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD ICLR 2023 Certified Minimax Unlearning with Generalization Rates and Deletion Capacity NeurIPS 2023 Certified Robust Neural Networks: Generalization and Corruption Resistance ICML 2023 Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning NeurIPS 2023 Compression, Generalization and Learning JMLR 2023 Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions ICLR 2023 Convolutional Persistence as a Remedy to Neural Model Analysis AISTATS 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Demystifying Disagreement-on-the-Line in High Dimensions ICML 2023 Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS 2023 Distribution Free Domain Generalization ICML 2023 Diverse Cotraining Makes Strong Semi-Supervised Segmentor ICCV 2023 Double-Weighting for Covariate Shift Adaptation ICML 2023 Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape ICML 2023 End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization L4DC 2023 Exponential Generalization Bounds with Near-Optimal Rates for L_q-Stable Algorithms ICLR 2023 Fast Convergence in Learning Two-Layer Neural Networks with Separable Data AAAI 2023 Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation ICML 2023 Federated Domain Generalization With Generalization Adjustment CVPR 2023 Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization NeurIPS 2023 Generalization Analysis for Contrastive Representation Learning ICML 2023 Generalization and Estimation Error Bounds for Model-based Neural Networks ICLR 2023 Generalization Bounds for Adversarial Contrastive Learning JMLR 2023 Generalization Bounds for Adversarial Metric Learning IJCAI 2023