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Titlebook: Neural Information Processing; 25th International C Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa Conference proceedings 2018 Springer Nat

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發(fā)表于 2025-3-21 18:15:49 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Neural Information Processing
副標題25th International C
編輯Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa
視頻videohttp://file.papertrans.cn/664/663575/663575.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Neural Information Processing; 25th International C Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa Conference proceedings 2018 Springer Nat
描述.The seven-volume set of LNCS 11301-11307,?constitutes the proceedings of the 25th International Conference on Neural Information Processing,?ICONIP 2018, held in Siem Reap, Cambodia, in December 2018..The 401?full papers presented were carefully?reviewed and selected from 575 submissions. The papers?address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains.?The third volume, LNCS 11303, is organized in topical sections on embedded learning, transfer learning, reinforcement learning, and other learning approaches..
出版日期Conference proceedings 2018
關(guān)鍵詞artificial intelligence; biomedical engineering; data mining; deep learning; hci; human-computer interact
版次1
doihttps://doi.org/10.1007/978-3-030-04182-3
isbn_softcover978-3-030-04181-6
isbn_ebook978-3-030-04182-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

書目名稱Neural Information Processing影響因子(影響力)




書目名稱Neural Information Processing影響因子(影響力)學(xué)科排名




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Neural Information Processing被引頻次




書目名稱Neural Information Processing被引頻次學(xué)科排名




書目名稱Neural Information Processing年度引用




書目名稱Neural Information Processing年度引用學(xué)科排名




書目名稱Neural Information Processing讀者反饋




書目名稱Neural Information Processing讀者反饋學(xué)科排名




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Hybridized Character-Word Embedding for Korean Traditional Document Translationding to supplement loss from unknown words with character embedding. Experimental results show that the proposed method is efficient to translate old Korean archives (Hanja) to modern Korean documents (Hangul).
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Conference proceedings 2018018, held in Siem Reap, Cambodia, in December 2018..The 401?full papers presented were carefully?reviewed and selected from 575 submissions. The papers?address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across differen
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Topic-Bigram Enhanced Word Embedding Modelding topic-bigram information. The topic relevance weights are updated with word embeddings simultaneously during the training process. To verify the validity and accuracy of the model, we conduct experiments on word analogy task and word similarity task. The results show that the TBWE model can achieve the better performance in both two tasks.
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Conference proceedings 2018s?address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains.?The third volume, LNCS 11303, is organized in topical sections on embedded learning, transfer learning, reinforcement learning, and other learning approaches..
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