Hideaki Ishibashi

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 18

Top Topics

Stopping Criterion

Top Venues

Decis. Support Syst.

Publications

Kotaro Sakamoto, Hideaki Ishibashi, Rei Sato, Shinichi Shirakawa, Youhei Akimoto, Hideitsu Hino
ATNAS: Automatic Termination for Neural Architecture Search. Neural Networks 166 (2023)
Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino
A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. AISTATS (2023)
Ryuji Watanabe, Hideaki Ishibashi, Tetsuo Furukawa
Visual analytics of set data for knowledge discovery and member selection support. Decis. Support Syst. 152 (2022)
Hideaki Ishibashi, Shotaro Akaho
Principal Component Analysis for Gaussian Process Posteriors. Neural Comput. 34 (5) (2022)
Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa
Multi-task manifold learning for small sample size datasets. Neurocomputing 473 (2022)
Kazuki Miyazaki, Shuhei Takano, Ryo Tsuno, Hideaki Ishibashi, Tetsuo Furukawa
Low-rank kernel decomposition for scalable manifold modeling. SCIS/ISIS (2022)
Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa
Multi-task manifold learning for small sample size datasets. CoRR (2021)
Ryuji Watanabe, Hideaki Ishibashi, Tetsuo Furukawa
Visual analytics of set data for knowledge discovery and member selection support. CoRR (2021)
Hideaki Ishibashi, Shotaro Akaho
Principal component analysis for Gaussian process posteriors. CoRR (2021)
Hideaki Ishibashi, Hideitsu Hino
Stopping Criterion for Active Learning Based on Error Stability. CoRR (2021)
Hideaki Ishibashi, Hideitsu Hino
Stopping criterion for active learning based on deterministic generalization bounds. CoRR (2020)
Hideaki Ishibashi, Hideitsu Hino
Stopping criterion for active learning based on deterministic generalization bounds. AISTATS (2020)
Hideaki Ishibashi
Visualization Method of Viewpoints Latent in a Dataset. ICONIP (3) (2018)
Hideaki Ishibashi, Masayoshi Era, Tetsuo Furukawa
Hierarchical Tensor Manifold Modeling for Multi-Group Analysis. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (11) (2018)
Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa
Multi-task Manifold Learning Using Hierarchical Modeling for Insufficient Samples. ICONIP (3) (2018)
Hideaki Ishibashi, Tetsuo Furukawa
Hierarchical Tensor SOM Network for Multilevel-Multigroup Analysis. Neural Process. Lett. 47 (3) (2018)
Hideaki Ishibashi, Tetsuo Furukawa
Self-Organizing Maps for Multi-system and Multi-view Datasets. SCIS&ISIS (2016)
Hideaki Ishibashi, Ryota Shinriki, Hirohisa Isogai, Tetsuo Furukawa
Multilevel-Multigroup Analysis Using a Hierarchical Tensor SOM Network. ICONIP (3) (2016)
Masato Tanosaki, Hideaki Ishibashi, Tongsheng Zhang, Yoshio Okada
Effective Connectivity Maps in the Swine Somatosensory Cortex Estimated from Electrocorticography and Validated with Intracortical Local Field Potential Measurements. Brain Connect. 4 (2) (2014)