FMQA optimizes MDR classification error rates to identify predefined high-order epistatic interactions in simulated genetic datasets within limited iterations.
Effectiveness of hybrid op- timization method for quantum annealing machines
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Stage-dependent encoding in FMQA black-box optimization, using one-hot for learning and domain-wall for search, improves residual error on discretized Rastrigin functions under finer discretization and higher dimensions compared to uniform encodings.
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High-Order Epistasis Detection Using Factorization Machine with Quadratic Optimization Annealing and MDR-Based Evaluation
FMQA optimizes MDR classification error rates to identify predefined high-order epistatic interactions in simulated genetic datasets within limited iterations.
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Stage-dependent integer-binary encoding in factorization-machine black-box optimization
Stage-dependent encoding in FMQA black-box optimization, using one-hot for learning and domain-wall for search, improves residual error on discretized Rastrigin functions under finer discretization and higher dimensions compared to uniform encodings.