Journals

• Yiming Tian, Takuya Maekawa, Joseph Korpela, Daichi Amagata, Takahiro Hara, Sakiko Matsumoto, and Ken Yoda. Automatic Identification of Differences in Behavioral Co-occurrence between Groups Animal Biotelemetry, volume 9, number 21, 2021.

Conferences

• Hayato Nakama, Daichi Amagata, and Takahiro Hara. Approximate Top-k Inner Product Join with a Proximity Graph Proceedings of IEEE International Conference on Big Data (IEEE BigData), pages 4468-4471, 2021. The 6th Workshop on Advances in High-Dimensional Big Data.
• Jun Murao, Kei Yonekawa, Mori Kurokawa, Daichi Amagata, Takuya Maekawa, and Takahiro Hara. Concept Drift Detection with Denoising Autoencoder in Incomplete Data Proceedings of EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, pages 541-552, 2021. The UMUM workshop.
• Daichi Amagata, Shohei Tsuruoka, Yusuke Arai, and Takahiro Hara. Feat-SKSJ: Fast and Exact Algorithm for Top-k Spatial-Keyword Similarity Join Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information System (SIGSPATIAL), pages 15-24, 2021. The first and second authors contributed equally to this research.
• Daichi Amagata and Takahiro Hara. Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item? Proceedings of the ACM Recommender Systems Conference (RecSys), pages 273-281, 2021. Some writing errors are corrected here. Slide is here. Code is here.
• Yusuke Arai, Daichi Amagata, Sumio Fujita, and Takahiro Hara. LGTM: A Fast and Accurate kNN Search Algorithm in High-dimensional Spaces. Proceedings of the International Conference on Database and Expert Systems Applications (DEXA), pages 220-231, 2021. Winner of the Best Paper Award
• Daichi Amagata and Takahiro Hara. Fast Density-Peaks Clustering: Multicore-based Parallelization Approach Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 49-61, 2021. A corrected version is here (we have added some condition to make the theoretical result hold and removed wrong sentences). Code is here.
• Daichi Amagata, Makoto Onizuka, and Takahiro Hara. Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 36-48, 2021. Full version is here. Slide is here. Code is here.