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Titlebook: Model Checking Software; 29th International S Georgiana Caltais,Christian Schilling Conference proceedings 2023 The Editor(s) (if applicabl

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發(fā)表于 2025-3-21 17:07:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Model Checking Software
副標(biāo)題29th International S
編輯Georgiana Caltais,Christian Schilling
視頻videohttp://file.papertrans.cn/636/635737/635737.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Model Checking Software; 29th International S Georgiana Caltais,Christian Schilling Conference proceedings 2023 The Editor(s) (if applicabl
描述This book constitutes the refereed proceedings of the 29th International Symposium on Model Checking Software, SPIN 2023, held in Paris, France, during April 26–27, 2023.?.The 9 full papers and 2 short papers included in this book were carefully reviewed and selected from 21 submissions. They were organized in topical sections as follows: binary decision diagrams, concurrency, testing,?synthesis, explicit-state model checking..
出版日期Conference proceedings 2023
關(guān)鍵詞model checking; cyber security; formal verification; cryptography; formal methods; runtime enforcement; au
版次1
doihttps://doi.org/10.1007/978-3-031-32157-3
isbn_softcover978-3-031-32156-6
isbn_ebook978-3-031-32157-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Conference proceedings 2023g April 26–27, 2023.?.The 9 full papers and 2 short papers included in this book were carefully reviewed and selected from 21 submissions. They were organized in topical sections as follows: binary decision diagrams, concurrency, testing,?synthesis, explicit-state model checking..
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978-3-031-32156-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Mini-Batch Variational Inference for Time-Aware Topic Modeling,ilar to neural networks. Our method was actually implemented with deep learning framework. The evaluation results show that we could improve test set perplexity by using document timestamps and also that our test perplexity was comparable with that of collapsed Gibbs sampling, which is less efficient in memory usage than the proposed inference.
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1860-1030 researchers have strived to determine the future development of energy consumption, infrastructure and technology resources...This book proposes a new agent-based approach to studying the devel978-3-7908-2544-2978-3-7908-2004-1Series ISSN 1860-1030 Series E-ISSN 2197-926X
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