vc dimension

PAC-learning for Strategic Classification JMLR 2023 PAC Verification of Statistical Algorithms COLT 2023 Private Everlasting Prediction NeurIPS 2023 Sample Complexity for Distributionally Robust Learning under chi-square divergence JMLR 2023 Sharper Bounds for ℓ_p Sensitivity Sampling ICML 2023 Structure of universal formulas NeurIPS 2023 Testing of Index-Invariant Properties in the Huge Object Model COLT 2023 The One-Inclusion Graph Algorithm is not Always Optimal COLT 2023 WL meet VC ICML 2023 Generalized Resubstitution for Classification Error Estimation JMLR 2022 Learnability of Competitive Threshold Models IJCAI 2022 Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes NeurIPS 2022 On Optimal Learning Under Targeted Data Poisoning NeurIPS 2022 On the Optimal Memorization Power of ReLU Neural Networks ICLR 2022 Oracle-Efficient Online Learning for Smoothed Adversaries NeurIPS 2022 PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency AISTATS 2022 Transductive Robust Learning Guarantees AISTATS 2022 Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes NeurIPS 2022 VC dimension of partially quantized neural networks in the overparametrized regime ICLR 2022 Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power NeurIPS 2022 Active Learning of Convex Halfspaces on Graphs NeurIPS 2021 Adversarially Robust Learning with Unknown Perturbation Sets COLT 2021 Efficient Coreset Constructions via Sensitivity Sampling ACML 2021 Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models NeurIPS 2021 PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes COLT 2021