| A Convex Formulation for Learning from Crowds. H Kajino, Y Tsuboi, H Kashima Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence …, 2012 | 117 | 2012 |
| Molecular hypergraph grammar with its application to molecular optimization H Kajino International Conference on Machine Learning, 3183-3191, 2019 | 100 | 2019 |
| Learning from crowds and experts H Kajino, Y Tsuboi, I Sato, H Kashima Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012 | 50 | 2012 |
| Preserving worker privacy in crowdsourcing H Kajino, H Arai, H Kashima Data Mining and Knowledge Discovery, 1-22, 2014 | 48 | 2014 |
| Clustering crowds H Kajino, Y Tsuboi, H Kashima Proceedings of the AAAI conference on Artificial Intelligence 27 (1), 1120-1127, 2013 | 45 | 2013 |
| Instance-privacy preserving crowdsourcing H Kajino, Y Baba, H Kashima Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 …, 2014 | 25 | 2014 |
| Bidirectional learning for time-series models with hidden units T Osogami, H Kajino, T Sekiyama International Conference on Machine Learning, 2711-2720, 2017 | 22 | 2017 |
| Towards stable symbol grounding with zero-suppressed state autoencoder M Asai, H Kajino Proceedings of the International Conference on Automated Planning and …, 2019 | 19 | 2019 |
| クラウドソーシングと機械学習 (< 特集> 知識の転移) 鹿島久嗣， 梶野洸 人工知能 27 (4), 381-388, 2012 | 18* | 2012 |
| Classical planning in deep latent space M Asai, H Kajino, A Fukunaga, C Muise Journal of Artificial Intelligence Research 74, 1599-1686, 2022 | 16 | 2022 |
| Cogra: Concept-drift-aware stochastic gradient descent for time-series forecasting K Miyaguchi, H Kajino Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4594-4601, 2019 | 16 | 2019 |
| A Functional Dynamic Boltzmann Machine. H Kajino IJCAI, 1987-1993, 2017 | 13* | 2017 |
| Quality control for crowdsourced POI collection S Kajimura, Y Baba, H Kajino, H Kashima Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia …, 2015 | 10 | 2015 |
| A differentiable point process with its application to spiking neural networks H Kajino International Conference on Machine Learning, 5226-5235, 2021 | 7 | 2021 |
| Active learning for multi-relational data construction H Kajino, A Kishimoto, A Botea, E Daly, S Kotoulas Proceedings of the 24th International Conference on World Wide Web, 560-569, 2015 | 7 | 2015 |
| Privacy-preserving crowdsourcing H Kajino Ph. D. Dissertation. Univ. of Tokyo, 2015 | 7 | 2015 |
| Neuron as an Agent S Ohsawa, K Akuzawa, T Matsushima, G Bezerra, Y Iwasawa, H Kajino, ... | 6 | 2018 |
| Link prediction in sparse networks by incidence matrix factorization S Yokoi, H Kajino, H Kashima Journal of Information Processing 25, 477-485, 2017 | 6 | 2017 |
| Intelligent application scenario testing and error detection AI Botea, L Shwartz, A Kishimoto, R Marinescu, HOU Yufang, H Kajino, ... US Patent 12,013,776, 2024 | 5 | 2024 |
| Classical planning in deep latent space M Asai, H Kajino, A Fukunaga, C Muise arXiv preprint arXiv:2107.00110, 2021 | 3 | 2021 |
Hisashi KashimaProfessor, Kyoto University在 i.kyoto-u.ac.jp 的电子邮件经过验证
