ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2507.19968
  4. Cited By
Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training

Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training

26 July 2025
Yue Hu
Zanxia Cao
Yingchao Liu
    ODL
ArXiv (abs)PDFHTMLGithub (1★)

Papers citing "Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training"

1 / 1 papers shown
Title
Escaping Saddle Points via Curvature-Calibrated Perturbations: A Complete Analysis with Explicit Constants and Empirical Validation
Escaping Saddle Points via Curvature-Calibrated Perturbations: A Complete Analysis with Explicit Constants and Empirical Validation
Faruk Alpay
Hamdi Alakkad
84
0
0
22 Aug 2025
1