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Titlebook: Advances in Artificial Intelligence; Selected Papers from Katsutoshi Yada,Daisuke Katagami,Hisashi Kashima Conference proceedings 2021 The

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發(fā)表于 2025-3-21 18:06:21 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Artificial Intelligence
期刊簡(jiǎn)稱Selected Papers from
影響因子2023Katsutoshi Yada,Daisuke Katagami,Hisashi Kashima
視頻videohttp://file.papertrans.cn/147/146713/146713.mp4
發(fā)行地址Provides recent research in artificial intelligence.Presents the selected papers presented at the Annual Conference of Japanese Society of Artificial Intelligence.Written by experts in the field
學(xué)科分類Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Advances in Artificial Intelligence; Selected Papers from Katsutoshi Yada,Daisuke Katagami,Hisashi Kashima Conference proceedings 2021 The
影響因子This book contains expanded versions of research papers presented at the international sessions of Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), which was held online in June 2020. The JSAI annual conferences are considered key events for our organization, and the international sessions held at these conferences play a key role for the society in its efforts to share Japan’s research on artificial intelligence with other countries. In recent years, AI research has proved of great interest to business people. The event draws both more and more presenters and attendees every year, including people of diverse backgrounds such as law and the social sciences, in additional to artificial intelligence. We are extremely pleased to publish this collection of papers as the research results of our international sessions.
Pindex Conference proceedings 2021
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發(fā)表于 2025-3-21 21:46:46 | 只看該作者
Conference proceedings 2021ndees every year, including people of diverse backgrounds such as law and the social sciences, in additional to artificial intelligence. We are extremely pleased to publish this collection of papers as the research results of our international sessions.
板凳
發(fā)表于 2025-3-22 01:32:38 | 只看該作者
https://doi.org/10.1007/978-3-319-55524-9asive essay dataset that is styled using the issue-based information system (IBIS). The experimental results show that the proposed approach is able to classify the nodes in online discussion structures accurately.
地板
發(fā)表于 2025-3-22 07:52:43 | 只看該作者
G. Anthony Reina,Ravi Panchumarthy multinomial classification emphasized the entire cloud structure, while the binary classification focused on cloud continuity. The results indicated accuracies of 71.00% and 65.37% for binary and multinomial classifications, respectively.
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Optimized U-Net for?Brain Tumor Segmentation data (i.e., transfer learning). Our results show that transfer from social media to live streaming is effective. However, the similarity measures we proposed show less correlation on the transferability prediction.
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發(fā)表于 2025-3-22 19:17:15 | 只看該作者
Xiangyu Li,Gongning Luo,Kuanquan Wang on the responsible case assignment, we propose an algorithm for revising a generated PROLEG rulebase so that the revised rulebase covers the representative precedents intended by lawmakers as well as the new exceptional case.
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發(fā)表于 2025-3-23 03:54:04 | 只看該作者
https://doi.org/10.1007/978-3-030-11726-9rix decomposition and sampling are discussed. The computability advantage over classical Birkhoff-von Neumann method is proved. The connection to traditional dynamic programming algorithm is discussed in terms of functional equations. Our work suggests a new hybrid quantum-classical approach to dynamic programming algorithms.
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發(fā)表于 2025-3-23 05:41:22 | 只看該作者
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