Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter

Yi Xu, Qihang Lin, Tianbao Yang

Nov-21-2025, 04:21:29 GMT–Neural Information Processing Systems

A common practice for solving non-strongly convex finite-sum problems by SVRG is to add a small strongly convex regularizer (e.g.,

artificial intelligence, convergence, machine learning, (18 more...)

Neural Information Processing Systems

Nov-21-2025, 04:21:29 GMT

Conferences PDF

Country:
- North America > United States
  - California > Los Angeles County
    - Long Beach (0.04)
  - Iowa > Johnson County
    - Iowa City (0.14)

Technology:
- Information Technology > Artificial Intelligence
  - Machine Learning > Statistical Learning (0.95)
  - Representation & Reasoning (0.95)

Duplicate Docs Excel Report

Title
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter

Similar Docs Excel Report more

Title	Similarity	Source
None found