Items where Author is "Bessiere, Christian"
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classification
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
classification machine learning
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
crawling
Huang, Hai ORCID: 0000-0003-1412-0567 and Gandon, Fabien (2021) Learning URI selection criteria to improve the crawling of linked open data (extended abstract). In: JCAI'20: Twenty-Ninth International Joint Conference on Artificial Intelligence Yokohama Yokohama, Japan January 7 - 15, 2021. International Joint Conferences on Artificial Intelligence, Yokohama, Japan, pp. 4730-4734. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/655)
FTRL
Huang, Hai ORCID: 0000-0003-1412-0567 and Gandon, Fabien (2021) Learning URI selection criteria to improve the crawling of linked open data (extended abstract). In: JCAI'20: Twenty-Ninth International Joint Conference on Artificial Intelligence Yokohama Yokohama, Japan January 7 - 15, 2021. International Joint Conferences on Artificial Intelligence, Yokohama, Japan, pp. 4730-4734. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/655)
linked RDF data
Huang, Hai ORCID: 0000-0003-1412-0567 and Gandon, Fabien (2021) Learning URI selection criteria to improve the crawling of linked open data (extended abstract). In: JCAI'20: Twenty-Ninth International Joint Conference on Artificial Intelligence Yokohama Yokohama, Japan January 7 - 15, 2021. International Joint Conferences on Artificial Intelligence, Yokohama, Japan, pp. 4730-4734. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/655)
machine learning
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
multi-instance
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
multi-label
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
multi-view learning data mining
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)
semi-supervised learning
Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)