RIKEN Center for Advanced Intelligence Project Succinct Information Processing Team
Team Director: Yasuo Tabei (D.Sc.)
Research Summary
We are at the forefront of data compression research. Specifically, we focus on a technology called 'succinct data structures', which supports various operations while keeping the data compressed. In today's world, there's an ongoing trend of data becoming more massive, and there's a demand for efficient processing methods. Succinct data structures enable the rapid and memory-efficient handling of large volumes of data. Through the application of this technology, we are advancing research in artificial intelligence and knowledge discovery aimed at efficiently processing large-scale data.
Research Subjects:
- Machine Learning
- Data mining
- Data compression
Main Research Fields
- Informatics
Related Research Fields
- Algorithm
- Data Structure
Selected Publications
- 1
Nishimoto, T., Kanda, S., Tabei, Y.:
"Optimal-time RLBWT construction in BWT-runs bounded space"
In Proceedings of the 49th International Colloquium on Automata, Languages, and Programming (ICALP), 2022 - 2
Nishimoto, T., Tabei, Y.:
"Optimal-time queries on BWT-runs compressed indexes"
In Proceedings of the 48th International Colloquium on Automata, Languages, and Programming (ICALP), 2021 - 3
Kanda, S., Tabei, Y.:
"Dynamic similarity search on integer sketches"
In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020 - 4
Kanda, S., Tabei, Y.:
"b-bit sketch trie: scalable similarity search on integer sketches"
In Proceedings of the 2019 IEEE International Conference on BigData (IEEE BigData), 2019 - 5
Tabei, Y., Yamanishi, Y., Pagh, R.:
"Space-efficient feature maps for string alignment kernels"
In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM), 2019 - 6
Tabei, Y., Simon, J. P.:
"Scalable similarity search for molecular descriptors"
In Proceedings of the 10th International Conference on Similarity Search and Applications, 2017 - 7
Tabei, Y., Saigo, H., Yamanishi, Y., Puglisi, S. J.:
"Scalable partial least squares regression on grammar-compressed data matrices"
In Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016
Related Links
Lab Members
Principal investigator
- Yasuo Tabei
- Team Director
Core members
- Takaaki Nishimoto
- Research Scientist
- Yoshitaka Yamamoto
- Visiting Scientist
- Hiroto Saigo
- Visiting Scientist
- Koh Takeuchi
- Visiting Scientist
Contact Information
Nihonbashi 1-chome Mitsui Building, 15th floor,
1-4-1 Nihonbashi,
Chuo-ku, Tokyo
103-0027, Japan
Email: yasuo.tabei [at] riken.jp