Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes

Documenti analoghi

• From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning
  di: Zakerinia, Hossein, et al.
  Pubblicazione: (2025)
• From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD
  di: Lampert, Christoph H., et al.
  Pubblicazione: (2026)
• More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
  di: Zakerinia, Hossein, et al.
  Pubblicazione: (2024)
• PeFLL: Personalized Federated Learning by Learning to Learn
  di: Scott, Jonathan, et al.
  Pubblicazione: (2023)
• Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
  di: Zakerinia, Hossein, et al.
  Pubblicazione: (2025)