DTM-based filtrations H Anai, F Chazal, M Glisse, Y Ike, H Inakoshi, R Tinarrage, Y Umeda Topological Data Analysis: The Abel Symposium 2018, 33-66, 2020 | 56 | 2020 |
Learning multi-way relations via tensor decomposition with neural networks K Maruhashi, M Todoriki, T Ohwa, K Goto, Y Hasegawa, H Inakoshi, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 35 | 2018 |
Effective decision support for product configuration by using CBR H Inakoshi, S Okamoto, Y Ohta, N Yugami Proceedings of the Fourth International Conference on Case-Based Reasoning …, 2001 | 25 | 2001 |
Eric: extracting relations inferred from convolutions J Townsend, T Kasioumis, H Inakoshi Proceedings of the Asian Conference on Computer Vision, 2020 | 17 | 2020 |
Putting accountability of AI systems into practice BS Miguel, A Naseer, H Inakoshi Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 15 | 2021 |
Elite BackProp: Training Sparse Interpretable Neurons. T Kasioumis, J Townsend, H Inakoshi NeSy, 82-93, 2021 | 10 | 2021 |
A fast algorithm for matching planar maps with minimum Fréchet distances J Shigezumi, T Asai, H Morikawa, H Inakoshi Proceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics …, 2015 | 10 | 2015 |
Extraction Algorithms for Hierarchical Header Structures from Spreadsheets. K Goto, Y Ohta, H Inakoshi, N Yugami EDBT/ICDT Workshops, 179-188, 2016 | 6 | 2016 |
Effective decision support for product configuration by using CBR. Fujitsu Laboratories LTD H Inakoshi, S Okamoto, Y Ohta Technical Report, 2001 | 4 | 2001 |
Mining frequent partite episodes with partwise constraints T Katoh, S Tago, T Asai, H Morikawa, J Shigezumi, H Inakoshi International Workshop on New Frontiers in Mining Complex Patterns, 117-131, 2013 | 3 | 2013 |
EVIS: A fast and scalable episode matching engine for massively parallel data streams S Tago, T Asai, T Katoh, H Morikawa, H Inakoshi Database Systems for Advanced Applications: 17th International Conference …, 2012 | 3 | 2012 |
Chimera: Stream-oriented XML filtering/querying engine T Asai, S Tago, H Inakoshi, S Okamoto, M Takeda Database Systems for Advanced Applications: 15th International Conference …, 2010 | 3 | 2010 |
Automatic neural network search method for open set recognition L Sun, X Yu, L Wang, J Sun, H Inakoshi, K Kobayashi, H Kobashi 2019 IEEE International Conference on Image Processing (ICIP), 4090-4094, 2019 | 2 | 2019 |
Discovery of areas with locally maximal confidence from location data H Inakoshi, H Morikawa, T Asai, N Yugami, S Okamoto Database Systems for Advanced Applications: 19th International Conference …, 2014 | 2 | 2014 |
Discovery of emerging patterns from nearest neighbors H Inakoshi, T Ando, A Sato, S Okamoto Proceedings. International Conference on Machine Learning and Cybernetics 4 …, 2002 | 2 | 2002 |
Advanced Analytics for Intelligent Society N Yugami, N Igata, H Anai, H Inakoshi FUJITSU Sci. Tech. J 48 (2), 110-116, 2012 | 1 | 2012 |
大規模半構造データからの高速な知識発見システム: 効率良い木構造パターンの発見と照合 浅井達哉, 稲越宏弥, 岡本青史 電子情報通信学会誌= The journal of the Institute of Electronics, Information …, 2012 | 1 | 2012 |
大規模空間データからの最適領域集合の効率的な発見方法 森川裕章, 浅井達哉, 多湖真一郎, 稲越宏弥, 湯上伸弘, 岡本青史 第 73 回全国大会講演論文集 2011 (1), 561-562, 2011 | 1 | 2011 |
Studies on Geospatial Mobility Analysis of Regions and Trajectories from Location Data 稲越宏弥 北海道大学, 2020 | | 2020 |
Discovery of Regularized Areas with Maximal Confidence from Location Data H Inakoshi, T Asai, T Kida, H Arimura Transactions of the Japanese Society for Artificial Intelligence 34 (3), D …, 2019 | | 2019 |