Yuji Kawamata

According to our database, Yuji Kawamata authored at least 9 papers between 2024 and 2026.

Collaborative distances:

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

2026

Single-Round Clustered Federated Learning via Data Collaboration Analysis for Non-IID Data.

Sota Sugawara, Yuji Kawamata, Akihiro Toyoda, Tomoru Nakayama, Yukihiko Okada

CoRR, January, 2026

Estimation of conditional average treatment effects on distributed confidential data.

Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura, Tetsuya Sakurai

Expert Syst. Appl., 2026

2025

A new type of federated clustering: A non-model-sharing approach.

Yuji Kawamata, Kaoru Kamijo, Masateru Kihira, Akihiro Toyoda, Tomoru Nakayama, Akira Imakura, Tetsuya Sakurai, Yukihiko Okada

CoRR, June, 2025

Anomaly Detection in Double-entry Bookkeeping Data by Federated Learning System with Non-model Sharing Approach.

Sota Mashiko, Yuji Kawamata, Tomoru Nakayama, Tetsuya Sakurai, Yukihiko Okada

CoRR, January, 2025

A Reliable Decision Support Framework for SME Default Prediction Using Uncertainty-Aware Bayesian GEV Regression.

Kaito Terada, Keiji Abe, Toshihiko Takeda, Yuji Kawamata, Ryoki Motai, Yukihiko Okada

Proceedings of the IEEE International Conference on Big Data, 2025

DC-CP: Data Collaboration Conformal Prediction from Model Training to Conformal Prediction in Single-Round Communication While Preserving Privacy.

Tomoru Nakayama, Yuji Kawamata, Akira Imakura, Yukihiko Okada

Proceedings of the IEEE International Conference on Big Data, 2025

2024

Collaborative causal inference on distributed data.

Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura, Tetsuya Sakurai

Expert Syst. Appl., 2024

Estimation of conditional average treatment effects on distributed data: A privacy-preserving approach.

Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura, Tetsuya Sakurai

CoRR, 2024

An explainable framework based on counterfactual explanations for multi-class financial distress prediction of small and medium enterprises.

Renon Ando, Yuji Kawamata, Toshihiko Takeda, Yukihiko Okada

Proceedings of the IEEE International Conference on Big Data, 2024