Poster Session (PSb-46～PSb-91)

[PSb-61] Learning Hamiltonian of black-box optimization problems for annealing machines with sparse graph structure

*Yuya Seki¹, Ryo Tamura^2,3, Shu Tanaka^4,5,6,7 (1. Graduate School of Science and Technology, Keio University, 2. International Center for Materials Nanoarchitectonics, National Institute for Materials Science, 3. Graduate School of Frontier Sciences, The University of Tokyo, 4. Department of Applied Physics and Physico-Informatics, Keio University, 5. Green Computing System Research Organization, Waseda University, 6. International Research Frontiers Initiative, Tokyo Institute of Technology, 7. Human Biology Microbiome Quantum Research Center (WPI-Bio2Q), Keio University)

Keywords:Quantum annealing, Machine learning, Combinatorial optimization problems, Black-box optimization, Inverse problem