activity
20242026
collaborators

6 papers

cs.LG2026

Stage-dependent integer-binary encoding in factorization-machine black-box optimization

Ryo Ogawa, Mayumi Nakano, Yuya Seki +1

Black-box optimization (BBO) deals with problems where objective functions lack explicit analytical forms and are expensive to evaluate. Factorization machine with quadratic-optimi…

cs.LG2026

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…

cs.LG2026

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…

cond-mat.stat-mech2025

Black-box optimization using factorization and Ising machines

Ryo Tamura, Yuya Seki, Yuki Minamoto +4

Black-box optimization (BBO) is used in materials design, drug discovery, and hyperparameter tuning in machine learning. The world is experiencing several of these problems. In thi…

cs.LG2025

Initialization Method for Factorization Machine Based on Low-Rank Approximation for Constructing a Corrected Approximate Ising Model

Yuya Seki, Hyakka Nakada, Shu Tanaka

This paper presents an initialization method that can approximate a given approximate Ising model with a high degree of accuracy using a factorization machine (FM), a machine learn…

quant-ph2024

Can Constrained Quantum Annealing Be Effective in Noisy Quantum Annealers?

Ryoya Igata, Myonsok I, Yuya Seki +2

We investigate the performance of penalty-based quantum annealing (PQA) and constrained quantum annealing (CQA) in solving the graph partitioning problem under various noise models…