Adaptive optimization: parameter-free self-tuning algorithms beyond smoothness and convexity

KAKEN

About This Project

Japan Grant Number
JP24K20737 (JGN)
Funding Program
Grants-in-Aid for Scientific Research
Funding Organization
Japan Society for the Promotion of Science

Kakenhi Information

Project/Area Number
24K20737
Research Category
Grant-in-Aid for Early-Career Scientists
Allocation Type
  • Multi-year Fund
Review Section / Research Field
  • Basic Section 60020:Mathematical informatics-related
Research Institution
  • Kyushu University
Project Period (FY)
2024-04-01 〜 2028-03-31
Project Status
Granted
Budget Amount*help
4,550,000 Yen (Direct Cost: 3,500,000 Yen Indirect Cost: 1,050,000 Yen)

Research Abstract

This project aims at producing out-of-the-box parameter-free optimization algorithms for engineering applications. The focus is on "self-adaptive" methods that automatically tune parameters at execution time without subroutines. Main challenges involve nonconvexity and embracing Newton-type methods.

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