| Adaptive weight decay for deep neural networks K Nakamura, BW Hong IEEE Access 7, 118857-118865, 2019 | 65 | 2019 |
| Learning-Rate Annealing Methods for Deep Neural Networks K Nakamura, B Derbel, KJ Won, BW Hong s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021 | 50 | 2021 |
| Deception game: Closing the safety-learning loop in interactive robot autonomy H Hu, Z Zhang, K Nakamura, A Bajcsy, JF Fisac 7th Annual Conference on Robot Learning, 2023 | 10 | 2023 |
| Simulation of brassiere-wearing figures using multi-regression models and its evaluation DE Choi, K Nakamura, T Kurokawa Journal of the Textile Machinery Society of Japan 58 (6), T68-T75, 2005 | 10 | 2005 |
| Stochastic batch size for adaptive regularization in deep network optimization K Nakamura, S Soatto, BW Hong Pattern Recognition 129, 108776, 2022 | 7 | 2022 |
| Fast-convergence superpixel algorithm via an approximate optimization K Nakamura, BW Hong Journal of Electronic Imaging 25 (5), 053035-053035, 2016 | 7 | 2016 |
| Analysis and classification of three-dimensional breast shape using human body model DE CHOI, K NAKAMURA, T KUROKAWA Journal of Textile Engineering 52 (6), 243-251, 2006 | 7 | 2006 |
| Block-cyclic stochastic coordinate descent for deep neural networks K Nakamura, S Soatto, BW Hong Neural Networks 139, 348-357, 2021 | 5 | 2021 |
| Hierarchical image segmentation via recursive superpixel with adaptive regularity K Nakamura, BW Hong Journal of Electronic Imaging 26 (6), 061602-061602, 2017 | 5 | 2017 |
| Learning-aware safety for interactive autonomy H Hu, Z Zhang, K Nakamura, A Bajcsy, JF Fisac arXiv preprint arXiv:2309.01267, 2023 | 4 | 2023 |
| A Continual Learning algorithm based on Orthogonal Gradient Descent beyond Neural Tangent Kernel regime DE Lee, K Nakamura, JH Tak, BW Hong IEEE Access, 2023 | 3 | 2023 |
| Stabilization of generative adversarial networks via noisy scale-space K Nakamura, S Korman, BW Hong Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 3 | 2021 |
| Generative adversarial networks via a composite annealing of noise and diffusion K Nakamura, S Korman, BW Hong Pattern Recognition 146, 110034, 2024 | 2 | 2024 |
| Regularization in network optimization via trimmed stochastic gradient descent with noisy label K Nakamura, BS Sohn, KJ Won, BW Hong IEEE Access 10, 34706-34715, 2022 | 2 | 2022 |
| An isomorphic polygon model for describing human body shape K Nakamura, T Kurokawa The 6th international conference on information technology and applications …, 2009 | 2 | 2009 |
| Preparation of 3D-Coordinate from Chemical Structural Formula K Nakamura, N Tomioka, A Itai JCPE Journal 12 (3), 177-184, 2000 | 2 | 2000 |
| Improving Prediction Power in Simulation of Brassiere-Wearing Figures C Dong-Eun, N Kensuke, K Takao センターニュース/京都工芸繊維大学地域共同研究センター, 京都工芸繊維大学インキュベー …, 2005 | 1 | 2005 |
| Generalizing Safety Beyond Collision-Avoidance via Latent-Space Reachability Analysis K Nakamura, L Peters, A Bajcsy arXiv preprint arXiv:2502.00935, 2025 | | 2025 |
| Splitting of Composite Neural Networks via Proximal Operator With Information Bottleneck SI Han, K Nakamura, BW Hong IEEE Access, 2023 | | 2023 |
| Training Generative Adversarial Networks with first-order MAML JH Tak, K Nakamura, B Derbel, BW Hong 대한전자공학회 학술대회, 2844-2846, 2022 | | 2022 |
