Gradient Noise Convolution (GNC): Smoothing Loss Function for Distributed Large-Batch SGD. - Kosuke Haruki; Taiji Suzuki; Yohei Hamakawa; Takeshi Toda; Ryuji Sakai; Masahiro Ozawa; Mitsuhiro Kimura (CoRR, 2019)

Correlation-Diversified Portfolio Construction by Finding Maximum Independent Set in Large-Scale Market Graph. - Ryo Hidaka; Yohei Hamakawa; Jun Nakayama; Kosuke Tatsumura (IEEE Access, 2023)

Collaborative filtering based on nonnegative/binary matrix factorization. - Yukino Terui; Yuka Inoue; Yohei Hamakawa; Kosuke Tatsumura; Kazue Kudo (CoRR, 2024)

Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines. - Kosuke Tatsumura; Yohei Hamakawa; Masaya Yamasaki; Koji Oya; Hiroshi Fujimoto (CoRR, 2024)

Machine Learning-assisted High-speed Combinatorial Optimization with Ising Machines for Dynamically Changing Problems. - Yohei Hamakawa; Tomoya Kashimata; Masaya Yamasaki; Kosuke Tatsumura (CoRR, 2025)

Real-Time Black-Box Optimization for Dynamic Discrete Environments Using Embedded Ising Machines. - Tomoya Kashimata; Yohei Hamakawa; Masaya Yamasaki; Kosuke Tatsumura (CoRR, 2025)