3 papers
cs.LG2025
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…
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-ph2025
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…