| A genetic programming approach to designing convolutional neural network architectures M Suganuma, S Shirakawa, T Nagao Proceedings of the genetic and evolutionary computation conference, 497-504, 2017 | 771 | 2017 |
| Evaluation of speech-to-gesture generation using bi-directional LSTM network D Hasegawa, N Kaneko, S Shirakawa, H Sakuta, K Sumi Proceedings of the 18th International Conference on Intelligent Virtual …, 2018 | 142 | 2018 |
| Adaptive stochastic natural gradient method for one-shot neural architecture search Y Akimoto, S Shirakawa, N Yoshinari, K Uchida, S Saito, K Nishida International Conference on Machine Learning, 171-180, 2019 | 111 | 2019 |
| Evolution of deep convolutional neural networks using cartesian genetic programming M Suganuma, M Kobayashi, S Shirakawa, T Nagao Evolutionary computation 28 (1), 141-163, 2020 | 94 | 2020 |
| Evolutionary image segmentation based on multiobjective clustering S Shirakawa, T Nagao 2009 IEEE congress on evolutionary computation, 2466-2473, 2009 | 90 | 2009 |
| Graph structured program evolution S Shirakawa, S Ogino, T Nagao Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 58 | 2007 |
| これからの強化学習 牧野， 澁谷， 長史， 白川， 浅田 (No Title), 2016 | 53 | 2016 |
| CMA-ES with margin: Lower-bounding marginal probability for mixed-integer black-box optimization R Hamano, S Saito, M Nomura, S Shirakawa Proceedings of the genetic and evolutionary computation conference, 639-647, 2022 | 46 | 2022 |
| Speech-to-gesture generation: A challenge in deep learning approach with bi-directional LSTM K Takeuchi, D Hasegawa, S Shirakawa, N Kaneko, H Sakuta, K Sumi Proceedings of the 5th International Conference on Human Agent Interaction …, 2017 | 40 | 2017 |
| Dynamic optimization of neural network structures using probabilistic modeling S Shirakawa, Y Iwata, Y Akimoto Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 33 | 2018 |
| Dynamic ant programming for automatic construction of programs S Shirakawa, S Ogino, T Nagao IEEJ transactions on electrical and electronic engineering 3 (5), 540-548, 2008 | 31 | 2008 |
| Automatic berthing using supervised learning and reinforcement learning S Shimizu, K Nishihara, Y Miyauchi, K Wakita, R Suyama, A Maki, ... Ocean Engineering 265, 112553, 2022 | 26 | 2022 |
| Genetic image network (GIN): Automatically construction of image processing algorithm S Shirakawa, T Nagao Proceedings of the International Workshop on Advanced Image Technology …, 2007 | 26 | 2007 |
| Optimization of an H0 photonic crystal nanocavity using machine learning R Abe, T Takeda, R Shiratori, S Shirakawa, S Saito, T Baba Optics Letters 45 (2), 319-322, 2020 | 23 | 2020 |
| Bag of local landscape features for fitness landscape analysis S Shirakawa, T Nagao Soft Computing 20 (10), 3787-3802, 2016 | 20 | 2016 |
| Genetic image network for image classification S Shirakawa, S Nakayama, T Nagao Workshops on Applications of Evolutionary Computation, 395-404, 2009 | 19 | 2009 |
| Designing convolutional neural network architectures using cartesian genetic programming M Suganuma, S Shirakawa, T Nagao Deep Neural Evolution: Deep Learning with Evolutionary Computation, 185-208, 2020 | 17 | 2020 |
| Evolution of sorting algorithm using graph structured program evolution. S Shirakawa, T Nagao Proceedings of the 2007 IEEE International Conference on Systems, Man and …, 2007 | 17 | 2007 |
| Hierarchical feature construction for image classification using genetic programming M Suganuma, D Tsuchiya, S Shirakawa, T Nagao 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016 | 16 | 2016 |
| Genetic Image Network による画像変換の自動構築 白川真一， 荻野慎太郎， 長尾智晴 情報処理学会論文誌数理モデル化と応用 (TOM) 48 (SIG19 (TOM19)), 117-126, 2007 | 16 | 2007 |
