Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning

Ähnliche Einträge

• Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility
  von: Lee, Hoil, et al.
  Veröffentlicht: (2022)
• Learning Over-Relaxation Policies for ADMM with Convergence Guarantees
  von: Lin, Junan, et al.
  Veröffentlicht: (2026)
• The Normal-Generalised Gamma-Pareto process: A novel pure-jump Lévy process with flexible tail and jump-activity properties
  von: Ayed, Fadhel, et al.
  Veröffentlicht: (2020)
• Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior
  von: Ayed, Fadhel, et al.
  Veröffentlicht: (2019)
• Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay
  von: Laus, Hannah, et al.
  Veröffentlicht: (2025)