Ai Kagawa

According to our database, Ai Kagawa authored at least 9 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Federated Learning Driven Multi-Modal User Scheduling for 5G Communication Systems.

Ai Kagawa, Imtiaz Ahmed

Proceedings of the 23rd Consumer Communications & Networking Conference, 2026

2025

Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference.

Ayush Khot, Miruna Oprescu, Maresa Schröder, Ai Kagawa, Xihaier Luo

CoRR, October, 2025

Bilevel-Optimized Clustered and Distributed Federated Learning Secured by Blockchain for Building Energy Forecasting.

Ai Kagawa, Judy Min, Nancy Min

Proceedings of the International Conference on Machine Learning and Applications, 2025

2024

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events.

Ayush Khot, Xihaier Luo, Ai Kagawa, Shinjae Yoo

CoRR, 2024

Privacy-Preserving Federated Learning for Science: Challenges and Research Directions.

Kibaek Kim, Krishnan Raghavan, Olivera Kotevska, Matthieu Dorier, Ravi K. Madduri, Minseok Ryu, Todd S. Munson, Robert Ross, Thomas Flynn, Ai Kagawa, Byung-Jun Yoon, Christian Engelmann, Farzad Yousefian

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats.

Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Van Dam, Deyu Lu

Proceedings of the International Conference on Machine Learning and Applications, 2023

2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

Francis J. Alexander, James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon

Int. J. High Perform. Comput. Appl., 2021

2019

REPR: Rule-Enhanced Penalized Regression.

Jonathan Eckstein, Ai Kagawa, Noam Goldberg

INFORMS J. Optim., April, 2019

2017

Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement.

Jonathan Eckstein, Noam Goldberg, Ai Kagawa

Proceedings of the 34th International Conference on Machine Learning, 2017