Fast-convergence superpixel algorithm via an approximate optimization. - Kensuke Nakamura 001; Byung-Woo Hong (J. Electronic Imaging, 2016)

Hierarchical image segmentation via recursive superpixel with adaptive regularity. - Kensuke Nakamura 001; Byung-Woo Hong (J. Electronic Imaging, 2017)

Adaptive Weight Decay for Deep Neural Networks. - Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2019)

Regularization in neural network optimization via trimmed stochastic gradient descent with noisy label. - Kensuke Nakamura 001; Byung-Woo Hong (CoRR, 2020)

Stabilization of generative adversarial networks via noisy scale-space. - Kensuke Nakamura 001; Simon Korman; Byung-Woo Hong (CoRR, 2021)

Block-cyclic stochastic coordinate descent for deep neural networks. - Kensuke Nakamura 001; Stefano Soatto; Byung-Woo Hong (Neural Networks, 2021)

Regularization in Network Optimization via Trimmed Stochastic Gradient Descent With Noisy Label. - Kensuke Nakamura 001; Bong-Soo Sohn; Kyoung-Jae Won; Byung-Woo Hong (IEEE Access, 2022)

Stochastic batch size for adaptive regularization in deep network optimization. - Kensuke Nakamura 001; Stefano Soatto; Byung-Woo Hong (Pattern Recognit., 2022)

A Continual Learning Algorithm Based on Orthogonal Gradient Descent Beyond Neural Tangent Kernel Regime. - Da Eun Lee; Kensuke Nakamura 001; Jaeho Tak; Byung-Woo Hong (IEEE Access, 2023)

Splitting of Composite Neural Networks via Proximal Operator With Information Bottleneck. - Sang-Il Han; Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2024)

Generative adversarial networks via a composite annealing of noise and diffusion. - Kensuke Nakamura 001; Simon Korman; Byung-Woo Hong (Pattern Recognit., 2024)

Decoupled Latent Diffusion Model for Enhancing Image Generation. - Hyun-Tae Choi; Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2025)

Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation. - Kensuke Nakamura 001; Bong-Soo Sohn; Simon Korman; Byung-Woo Hong (IEEE Access, 2025)