Hideaki Ishibashi

According to our database, Hideaki Ishibashi authored at least 15 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

ATNAS: Automatic Termination for Neural Architecture Search.

Kotaro Sakamoto, Hideaki Ishibashi, Rei Sato, Shinichi Shirakawa, Youhei Akimoto, Hideitsu Hino

Neural Networks, September, 2023

A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets.

Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Principal Component Analysis for Gaussian Process Posteriors.

Hideaki Ishibashi, Shotaro Akaho

Neural Comput., 2022

Multi-task manifold learning for small sample size datasets.

Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa

Neurocomputing, 2022

Visual analytics of set data for knowledge discovery and member selection support.

Ryuji Watanabe, Hideaki Ishibashi, Tetsuo Furukawa

Decis. Support Syst., 2022

Low-rank kernel decomposition for scalable manifold modeling.

Kazuki Miyazaki, Shuhei Takano, Ryo Tsuno, Hideaki Ishibashi, Tetsuo Furukawa

Proceedings of the Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, 2022

2021

Stopping Criterion for Active Learning Based on Error Stability.

Hideaki Ishibashi, Hideitsu Hino

CoRR, 2021

2020

Stopping criterion for active learning based on deterministic generalization bounds.

Hideaki Ishibashi, Hideitsu Hino

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018

Hierarchical Tensor SOM Network for Multilevel-Multigroup Analysis.

Hideaki Ishibashi, Tetsuo Furukawa

Neural Process. Lett., 2018

Hierarchical Tensor Manifold Modeling for Multi-Group Analysis.

Hideaki Ishibashi, Masayoshi Era, Tetsuo Furukawa

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018

Multi-task Manifold Learning Using Hierarchical Modeling for Insufficient Samples.

Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa

Proceedings of the Neural Information Processing - 25th International Conference, 2018

Visualization Method of Viewpoints Latent in a Dataset.

Hideaki Ishibashi

Proceedings of the Neural Information Processing - 25th International Conference, 2018

2016

Self-Organizing Maps for Multi-system and Multi-view Datasets.

Hideaki Ishibashi, Tetsuo Furukawa

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

Multilevel-Multigroup Analysis Using a Hierarchical Tensor SOM Network.

Hideaki Ishibashi, Ryota Shinriki, Hirohisa Isogai, Tetsuo Furukawa

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2014

Effective Connectivity Maps in the Swine Somatosensory Cortex Estimated from Electrocorticography and Validated with Intracortical Local Field Potential Measurements.

Masato Tanosaki, Hideaki Ishibashi, Tongsheng Zhang, Yoshio Okada

Brain Connect., 2014