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Generalization Bounds

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TitleStatusHype
Neural Optimization Kernel: Towards Robust Deep Learning—0
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning—0
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization—0
Non-parametric Binary regression in metric spaces with KL loss—0
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels—0
Nonparametric Hawkes Processes: Online Estimation and Generalization Bounds—0
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models—0
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks—0
Nuclear Discrepancy for Active Learning—0
ON BREIMAN’S DILEMMA IN NEURAL NETWORKS: SUCCESS AND FAILURE OF NORMALIZED MARGINS—0
On Certified Generalization in Structured Prediction—0
On Combining Machine Learning with Decision Making—0
On Feature Diversity in Energy-based Models—0
On Generalization and Regularization via Wasserstein Distributionally Robust Optimization—0
On Generalization Bounds for Deep Compound Gaussian Neural Networks—0
On Generalization Bounds for Neural Networks with Low Rank Layers—0
On Generalization Bounds for Projective Clustering—0
On Generalization Bounds of a Family of Recurrent Neural Networks—0
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning—0
On how to avoid exacerbating spurious correlations when models are overparameterized—0
On Leave-One-Out Conditional Mutual Information For Generalization—0
Online Optimization for Learning to Communicate over Time-Correlated Channels—0
Online-to-PAC Conversions: Generalization Bounds via Regret Analysis—0
Online-to-PAC generalization bounds under graph-mixing dependencies—0
On Localized Discrepancy for Domain Adaptation—0
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