2 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
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…