Journals

• Yuchen Ji, Daichi Amagata, Yuya Sasaki, and Takahiro Hara. PolyCard: A Learned Cardinality Estimator for Intersection Queries on Spatial Polygons Journal of Intelligent Information Systems, volume 63, pages 873-891, 2025.

Conferences

• Reon Uemura and Daichi Amagata. IVF++: A Flexible and Efficient Algorithm for Approximate Nearest Neighbor Search under Attribute Constraint Proceedings of the IEEE International Conference on Big Data, pages xxx-xxx, 2025. Workshop on New Generation Databases and Data-Empowering Technologies in Big Data Era
• Daichi Amagata and Jimin Lee Top-k Range Search on Weighted Interval Data Proceedings of the International Symposium on Spatial and Temporal Data (SSTD), pages 218-228, 2025. The authors contributed to this work equally. Best selection of SSTD 2025
• Ryo Shirai, Ryo Imai, and Daichi Amagata Target and Non-target Category Classification from GPS and Check-in Data Proceedings of the International Symposium on Spatial and Temporal Data (SSTD), pages 181-191, 2025. Industrial Track. Code is here.
• Daichi Amagata, Kazuyoshi Aoyama, Keito Kido, and Sumio Fujita How to Mine Potentially Popular Items? A Reverse MIPS-based Approach Proceedings of the International Conference on Scientific and Statistical Database Management (SSDBM), pages 9:1-9:11, 2025. The first two authors contributed to this work equally. arXiv version is here.
• Daichi Amagata, Kazuyoshi Aoyama, Keito Kido, and Sumio Fujita Approximate Reverse k-Ranks Queries in High Dimensions Proceedings of the International Conference on Scientific and Statistical Database Management (SSDBM), pages 17:1-17:6, 2025. The first two authors contributed to this work equally. arXiv version is here.
• Keito Kido, Daichi Amagata, and Takahiro Hara. Fast Approximation Algorithm for Euclidean Minimum Spanning Tree Building in High Dimensions Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages 432-443, 2025. Special Session: Data Science: Foundations and Applications (DSFA) Code is here.
• Daichi Amagata **Random Sampling over Spatial Range Joins Proceedings of the IEEE International Conference on Data Engineering (ICDE), pages 2080–2093, 2025. arXiv version is here. Code is here. Poster is here. Slide is here.**

Pre-print

• Tomohiro Yamashita, Daichi Amagata, and Yusuke Matsui. How Should We Evaluate Data Deletion in Graph-Based ANN Indexes? NeurIPS 2025 Workshop on Machine Learning for Systems