2 citations · 3 across the 4 of their papers we have counts for
4 papers
Statistics of Min-max Normalized Eigenvalues in Random Matrices
Hyakka Nakada, Shu Tanaka
Random matrix theory has played an important role in various areas of pure mathematics, mathematical physics, and machine learning. From a practical perspective of data science, in…
Systematic and Efficient Construction of Quadratic Unconstrained Binary Optimization Forms for High-order and Dense Interactions
Hyakka Nakada, Shu Tanaka
Quantum Annealing (QA) can efficiently solve combinatorial optimization problems whose objective functions are represented by Quadratic Unconstrained Binary Optimization (QUBO) for…
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…
Machine learning supported annealing for prediction of grand canonical crystal structures
Yannick Couzinie, Yuya Seki, Yusuke Nishiya +4
This study investigates the application of Factorization Machines with Quantum Annealing (FMQA) to address the crystal structure problem (CSP) in materials science. FMQA is a black…