2 citations · 3 across the 8 of their papers we have counts for
10 papers
Ising-Machine-Assisted Large Neighborhood Search with Flexibly Tunable Subproblem Size
Koshiro Fujimoto, Masashi Yamashita, Shu Tanaka
Ising machines are heuristic solvers for combinatorial optimization, but their solution quality can degrade when large-scale constrained problems are solved directly. Ising-machine…
Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
Taiga Hayashi, Yuya Seki, Kotaro Terada +3
Factorization machine with quadratic-optimization annealing (FMQA) is a black-box optimization method that combines a factorization machine (FM) surrogate with QUBO-based search by…
Parallelizable Search-Space Decomposition for Large-Scale Combinatorial Optimization Problems Using Ising Machines
Eiji Kawase, Shuta Kikuchi, Hideaki Tamai +1
Combinatorial optimization problems are crucial in industry. However, many COPs are NP-hard, causing the search space to grow exponentially with problem size and rendering large-sc…
High-Order Epistasis Detection Using Factorization Machine with Quadratic Optimization Annealing and MDR-Based Evaluation
Shuta Kikuchi, Shu Tanaka
Detecting high-order epistasis is a fundamental challenge in genetic association studies due to the combinatorial explosion of candidate locus combinations. Although multifactor di…
Extending Sample Persistence Variable Reduction for Constrained Combinatorial Optimization Problems
Shunta Ide, Shuta Kikuchi, Shu Tanaka
Constrained combinatorial optimization problems (CCOPs) are challenging to solve due to the exponential growth of the solution space. When tackled with Ising machines, constraints…
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…
Effectiveness of Hybrid Optimization Method for Quantum Annealing Machines
Shuta Kikuchi, Nozomu Togawa, Shu Tanaka
To enhance the performance of quantum annealing machines, several methods have been proposed to reduce the number of spins by fixing spin values through preprocessing. We proposed…
SWIFT-FMQA: Enhancing Factorization Machine with Quadratic-Optimization Annealing via Sliding Window
Mayumi Nakano, Yuya Seki, Shuta Kikuchi +1
Black-box (BB) optimization problems aim to identify an input that maximizes or minimizes the output of a function (the BB function) whose input-output relationship is unknown. Fac…
Quantitative analysis of the effectiveness of mid-anneal measurement in quantum annealing
Keita Takahashi, Shu Tanaka
Quantum annealing is a promising metaheuristic for solving constrained combinatorial optimization problems. However, parameter tuning difficulties and hardware noise often prevent…
Performance of Domain-Wall Encoding in Digital Ising Machine
Shuta Kikuchi, Kotaro Takahashi, Shu Tanaka
To tackle combinatorial optimization problems using an Ising machine, the objective function and constraints must be mapped onto a quadratic unconstrained binary optimization (QUBO…