generalization bound

Nearly-tight Bounds for Deep Kernel Learning ICML 2023 Neural Networks and the Chomsky Hierarchy ICLR 2023 Neural Networks Efficiently Learn Low-Dimensional Representations with SGD ICLR 2023 NICO++: Towards Better Benchmarking for Domain Generalization CVPR 2023 Norm-based Generalization Bounds for Sparse Neural Networks NeurIPS 2023 On Certified Generalization in Structured Prediction NeurIPS 2023 On Generalization Bounds for Projective Clustering NeurIPS 2023 On Generalization of Decentralized Learning with Separable Data AISTATS 2023 Online Constrained Meta-Learning: Provable Guarantees for Generalization NeurIPS 2023 On student-teacher deviations in distillation: does it pay to disobey? NeurIPS 2023 On the Capacity Limits of Privileged ERM AISTATS 2023 On the Generalization Properties of Diffusion Models NeurIPS 2023 On the Implicit Bias of Linear Equivariant Steerable Networks NeurIPS 2023 On the Role of Generalization in Transferability of Adversarial Examples UAI 2023 On the Stability and Generalization of Triplet Learning AAAI 2023 Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NeurIPS 2023 Outlier Robust Adversarial Training ACML 2023 PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction NeurIPS 2023 PAC-Bayesian Generalization Bounds for Adversarial Generative Models ICML 2023 PAC-Bayesian Offline Contextual Bandits With Guarantees ICML 2023 PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization NeurIPS 2023 PAC-tuning: Fine-tuning Pre-trained Language Models with PAC-driven Perturbed Gradient Descent EMNLP 2023 Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks ICML 2023 Precise asymptotic generalization for multiclass classification with overparameterized linear models NeurIPS 2023 Provable Pathways: Learning Multiple Tasks over Multiple Paths AAAI 2023