A black-box optimization method with polynomial-based kernels and quadratic-optimization annealing
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908631655514112 |
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| author | Minamoto, Yuki Sakamoto, Yuya |
| author_facet | Minamoto, Yuki Sakamoto, Yuya |
| contents | We introduce kernel-QA, a black-box optimization (BBO) method that constructs surrogate models analytically using low-order polynomial kernels within a quadratic unconstrained binary optimization (QUBO) framework, enabling efficient utilization of Ising machines. The method has been evaluated on artificial landscapes, ranging from uni-modal to multi-modal, with input dimensions extending to 80 for real variables and 640 for binary variables. The results demonstrate that kernel-QA is particularly effective for optimizing black-box functions characterized by local minima and high-dimensional inputs, showcasing its potential as a robust and scalable BBO approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_04225 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A black-box optimization method with polynomial-based kernels and quadratic-optimization annealing Minamoto, Yuki Sakamoto, Yuya Optimization and Control We introduce kernel-QA, a black-box optimization (BBO) method that constructs surrogate models analytically using low-order polynomial kernels within a quadratic unconstrained binary optimization (QUBO) framework, enabling efficient utilization of Ising machines. The method has been evaluated on artificial landscapes, ranging from uni-modal to multi-modal, with input dimensions extending to 80 for real variables and 640 for binary variables. The results demonstrate that kernel-QA is particularly effective for optimizing black-box functions characterized by local minima and high-dimensional inputs, showcasing its potential as a robust and scalable BBO approach. |
| title | A black-box optimization method with polynomial-based kernels and quadratic-optimization annealing |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2501.04225 |