SOTAVerified

Generalization Bounds

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 626–650 of 686 papers

TitleStatusHype
Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side KnowledgeCode0
Integral Probability Metrics PAC-Bayes BoundsCode0
Towards Understanding Generalization of Macro-AUC in Multi-label LearningCode0
Generalization Bounds For Meta-Learning: An Information-Theoretic AnalysisCode0
Random deep neural networks are biased towards simple functionsCode0
Comparing Comparators in Generalization BoundsCode0
PAC-Bayesian Generalization Bounds for Adversarial Generative ModelsCode0
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient DescentCode0
A PAC-Bayesian Framework for Optimal Control with Stability GuaranteesCode0
Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and OptimizationCode0
Learnability of Competitive Threshold ModelsCode0
Adversarial Transform Particle FiltersCode0
Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and SpecificityCode0
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression ApproachCode0
Learning an Explicit Hyperparameter Prediction Function Conditioned on TasksCode0
Uniform convergence may be unable to explain generalization in deep learningCode0
Towards Size-Independent Generalization Bounds for Deep Operator NetsCode0
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization GuaranteesCode0
Robust Generalization despite Distribution Shift via Minimum Discriminating InformationCode0
Approximation and Learning with Deep Convolutional Models: a Kernel PerspectiveCode0
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform StabilityCode0
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural NetworksCode0
Rethinking Breiman's Dilemma in Neural Networks: Phase Transitions of Margin DynamicsCode0
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient DescentCode0
On Cold Posteriors of Probabilistic Neural Networks: Understanding the Cold Posterior Effect and A New Way to Learn Cold Posteriors with Tight Generalization GuaranteesCode0
Show:102550
← PrevPage 26 of 28Next →

No leaderboard results yet.