Presentation information

Interactive Session

[4Rin1] Interactive Session 2

Fri. Jun 7, 2019 9:00 AM - 10:40 AM Room R (Center area of 1F Exhibition hall)

9:00 AM - 10:40 AM

[4Rin1-02] Initialization of a Search Space Considering a Budget for Black-box Optimization

〇Masahiro Nomura1, Kenshi Abe1 (1. CyberAgent, Inc.)

Keywords:Black-box Optimization

Black-box optimization is a problem of optimizing the objective function within the bounds of a given budget for evaluations.
In Black-box optimization, it is generally assumed that the calculation cost for evaluating one solution is large, so it is important to search efficiently with as few budgets as possible.
However, there is a problem that state-of-the-art black-box optimization methods such as Bayesian optimization and CMA-ES do not consider a budget.
In this paper, we aim to propose an initialization of a search space that takes a budget into account, dealing with the above problem.
We confirm that the proposed method shows good performance by experiments on the benchmark functions.