3 papers
cs.LG2026
Effectiveness of Binary Autoencoders for QUBO-Based Optimization Problems
Tetsuro Abe, Masashi Yamashita, Shu Tanaka
In black-box combinatorial optimization, objective evaluations are often expensive, so high quality solutions must be found under a limited budget. Factorization machine with quant…
quant-ph2026
Fair sampling with temperature-targeted QAOA based on quantum-classical correspondence theory
Tetsuro Abe, Shu Tanaka
In combinatorial optimization problems with degenerate ground states, fair sampling of degenerate solutions is essential. However, the quantum approximate optimization algorithm (Q…
cond-mat.stat-mech2025
Effectiveness of cardinality-return weighted maximum independent set approach for financial portfolio optimization
Keita Takahashi, Tetsuro Abe, Yasuhito Nakamura +3
The portfolio optimization problem is a critical issue in asset management and has long been studied. Markowitz's mean-variance model has fundamental limitations, such as the assum…