2024年
(査読あり)学術論文
Kotaro Ii, Hiroto Saigo, Yasuo Tabei: A Branch-and-Bound Approach to Efficient Classification and Retrieval of Documents. 13th International Conference on Pattern Recognition Applications and Methods, 2024.
2022年
(査読あり)学術論文
Takaaki Nishimoto, Shunsuke Kanda, Yasuo Tabei: Optimal-Time RLBWT Construction in BWT-runs Bounded Space, 49th International Colloquium on Automata, Languages, and Programming(ICALP), 2022
Takaaki Nishimoto, Yasuo Tabei: LZRR: LZ77 parsing with right reference, Information and Computation, 2022
2021年
(査読あり)学術論文
Koh Takeuchi, Masaaki Imaizumi, Shunsuke Kanda, Keisuke Fujii, Masakazu Ishihata, Yasuo Tabei, Frechet and Hausdorff Kernels for Trajectory Data Analysis, 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2021.
Mirai Takayanagi, Yasuo Tabei, Einoshin Suzuki, Hiroto Saigo: Sparse Nonnegative Interaction Models, IEEE Access, 2021.
Takaaki Nishimoto and Yasuo Tabei: Optimal-Time Queries on BWT-runs Compressed Indexes, 48th International Colloquium on Automata, Languages, and Programming (ICALP), 2021.
Takaaki Nishimoto and Yasuo Tabei: Enumeration of characteristic substrings in BWT-runs bounded space, 32nd International Conference on Combinatorial Pattern Matching (CPM), 2021.
本
マテリアルズインフォマティクスのためのデータ作成とその解析、応用事例, 技術情報協会, ISBN：978-4-86104-854-8
2020年
(査読あり)学術論文
Ryoichiro Yafune, Daisuke Sakuma, Yasuo Tabei, Noritaka Saito, Hiroto Saigo: Automatically Mining Relevant Variable Interactions via Sparse Bayesian Learning, International Conference on Pattern Recognition (ICPR), 2020.
Shunsuke Kanda and Yasuo Tabei: Dynamic Similarity Search on Integer Sketches, IEEE International Conference on Data Mining (ICDM), 2020.
Shunsuke Kanda, Koh Takeuchi, Keisuke Fujii, Yasuo Tabei: Succinct Trit-array Trie for Scalable Trajectory Similarity Search, 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), 2020.
Shunsuke Kanda, Dominik Köppl, Yasuo Tabei, Kazuhiro Morita, Masao Fuketa: Dynamic Path-decomposed Tries, ACM Journal of Experimental Algorithmics, 2020.
Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh: Space-efficient Feature Maps for String Alignment Kernels, Data Science and Engineering, 2020.
Yusuke Morikawa, Yasuhiro Ishihara, Takanori Ide, Eiji Moriyama, Taku Akita, Yasuo Tabei, Takehito Utsuro, Hiroshi Nakagawa: Classification of Time Series Measurement Data for Shift Control of Automatic Transmission of Vehicles Using Machine Learning Techniques, Society of Automotive Engineers World Congress Experience (SAE-WCX), 2020.
Takaaki Nishimoto, Yoshimasa Takabatake, Yasuo Tabei: A Compressed Dynamic Self-index for Highly repetitive Text Collections, Information and Computation, 104518, 2020.
Yasuo Tabei: Scalable Prediction of Compound‐protein Interaction on Compressed Molecular Fingerprints, Molecular Informatics, 2020.
2019年
(査読あり)学術論文
Yoshitaka Yamamoto, Yasuo Tabei, Koji Iwanuma: PARASOL: A Hybrid Approximation Approach for Scalable Frequent Itemset Mining in Streaming Data, Journal of Intelligent Information Systems, 2019.
Shunsuke Kanda and Yasuo Tabei: b-Bit Sketch Trie: Scalable Similarity Search on Integer Sketches, 2019 IEEE International Conference on BigData(IEEE BigData), 2019. (acceptance rate: (106/550=)19.2%)
Vo Nuguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Nishi, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi: Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction, 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019.
Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh: Space-efficient Feature Maps for String Alignment Kernels, 19th IEEE International Conference on Data Mining (ICDM), 2019. (acceptance rate: (194/1046=)18.5%)
Takaaki Nishimoto and Yasuo Tabei: Conversion from RLBWT to LZ77, 30th International Symposium on Combinatorial Pattern Matching (CPM), 2019. Link to the arXiv
Michio Iwata, Longhao Yuan, Qibin Zhao, Yasuo Tabei, Francois Berenger, Ryusuke Sawada, Sayaka Akiyoshi, Momoko Hamano and Yoshihiro Yamanishi: Predicting Drug-induced Transcriptome Responses of A Wide Range of Human Cell Lines by A Novel Tensor-Train Decomposition Algorithm, International Conference on Intelligence Systems for Molecular Biology (ISMB), 2019. (acceptance rate: (69/366=)18%) Link to the paper
Takaaki Nishimoto and Yasuo Tabei: LZRR: LZ77 Parsing with Right Reference, Data Compression Conference (DCC), 2019.
Yasuo Tabei, Masaaki Kotera, Ryusuke Sawada, Yoshihiro Yamanishi: Network-based Characterization of Drug-protein Interaction Signatures with A Space-efficient Approach, 17th Asia Pacific Bioinformatics Conference (APBC), 2019. Link to the paper
招待講演
圧縮情報処理による大規模バーチャルスクリーニング, 新学術領域研究「化学コミュニケーションのフロンティア」第3回若手シンポジウム, 2019年6月26日(水)
プレスリリース
自動車走行データ解析に関するAI技術の開発 リンク (2019年11月15日(木))
多様な細胞における薬物応答遺伝子発現を高精度に予測する新技術を開発 (2019年7月8日(月))
理化学研究所 九州工業大学 科学技術振興機構 QLifePro医療ニュース 日本経済新聞
2018年
(査読あり)学術論文
Mirai Takayanagi, Yasuo Tabei, Hiroto Saigo: Entire Regularization Path for Sparse Nonnegative Interaction Model, 2018 IEEE International Conference on Data Mining (ICDM). (acceptance rate: (189/984=)19%), 2018.
Takaaki Nishimoto, Yoshimasa Takabatake, Yasuo Tabei: A Dynamic Compressed Self-index for Highly Repetitive Text Collections, Data Compression Conference (DCC), 2018.
Ryusuke Sawada, Michio Iwata, Yasuo Tabei, Haruka Yamato, Yoshihiro Yamanishi: Predicting Inhibitory and Activatory Drug Targets by Chemically and Genetically Perturbed Transcriptome Signatures, Nature Scientific Reports, 2018. Link to the paper
Yasuo Tabei: Scalable Machine Learning on Compressed Data Representations, In Proceedings of the 2018 International Symposium on Information Theory and Its Applications.
招待講演
Scalable Machine Learning on Compressed Data Representations, 2018 International Symposium on Information Theory and Its Applications (ISITA), 2018年10月28日(日)-31日(水)
大規模バーチャルスクリーニングのための圧縮情報処理技術, 第２１回創薬インフォマティクス研究会, 2018年10月4日(木)
データ圧縮による効率的な人工知能技術, 理化学研究所エンジニアリングネットワークリトリート2018, 2018年3月1日(木)
効率的なvirtual screeningのための人工知能技術, 第21回産総研人工知能セミナー, 2018年2月23日(金)
2017年
(査読あり)学術論文
Yasuo Tabei and Simon J. Puglisi: Scalable Similarity Search for Molecular Descriptors, 10th International Conference on Similarity Search and Applications (SISAP), 2017. Link to the paper
Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi: Bayesian Dynamic Mode Decomposition, 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017. Link to the paper
Yoshihiro Yamanishi, Yasuo Tabei, Masaaki Kotera: Statistical Machine Learning for Agriculture and Human Healthcare based on Biomedical Big Data, Forum "Math-for-Industry" 2017.
招待講演
圧縮情報処理とその周辺, 情報処理学会九州支部報告会, 2017年5月12日(金)