学会优化 - 一个简短的概述
1Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
National science review
|July 15, 2024
概括
本综述涵盖了"学习优化"方法,这些方法使用过去的数据来改进算法配置,用于诸如机器学习优化等计算密集型任务.
科学领域:
- 计算科学 计算科学
- 机器学习 机器学习
- 算法优化的算法优化
背景情况:
- 实际的优化问题往往需要高度可配置的算法.
- 通过试错调整这些算法在计算上很昂贵,特别是在机器学习任务中.
- 现有的研究重点是通过从培训数据中学习来加速这种配置过程.
研究的目的:
- 审查和总结该领域的研究.
- 学习如何优化优化.
- 方法. 方法. 方法.
主要方法:
- 用机器学习来优化算法配置的研究的文献综述.
- 分类和分析在该领域内不同的方法.
- 学习如何优化优化.
- 一个范式. 一个范式.
主要成果:
- 的田野的领域.
- 学习如何优化优化.
- 在加速算法配置方面取得了重大进展.
- 已经开发了各种技术,以从训练实例中学习最佳参数.
结论:
- 学习优化提供了一个有希望的方向来降低配置复杂算法的计算成本.
- 在这个领域进行进一步的研究可以为计算密集型优化问题提供更高效的解决方案.
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