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Titlebook: Machine Learning, Optimization, and Data Science; 7th International Co Giuseppe Nicosia,Varun Ojha,Renato Umeton Conference proceedings 202

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發(fā)表于 2025-3-21 19:45:13 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Machine Learning, Optimization, and Data Science
副標題7th International Co
編輯Giuseppe Nicosia,Varun Ojha,Renato Umeton
視頻videohttp://file.papertrans.cn/621/620741/620741.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Machine Learning, Optimization, and Data Science; 7th International Co Giuseppe Nicosia,Varun Ojha,Renato Umeton Conference proceedings 202
描述.This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with ?the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021. .The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.?
出版日期Conference proceedings 2022
關鍵詞artificial intelligence; communication systems; computer networks; computer science; computer systems; co
版次1
doihttps://doi.org/10.1007/978-3-030-95470-3
isbn_softcover978-3-030-95469-7
isbn_ebook978-3-030-95470-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

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Machine Learning, Optimization, and Data Science978-3-030-95470-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620741.jpg
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,Deep Reinforcement Learning for?Optimal Energy Management of?Multi-energy Smart Grids,the production and storage units within the smart grid is formulated as a Partially Observable Markov Decision Process (POMDP), and is solved using an actor-critic Deep Reinforcement Learning algorithm. The framework is tested on a novel multi-energy residential microgrid model that encompasses elec
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A Machine Learning Approach to Daily Capacity Planning in E-Commerce Logistics,easing, which affects on-time delivery of regular parcels and groceries. An important constraint is the fact that a given number of delivery drivers have a limited amount of time and daily capacity, leading to the need for effective capacity planning. In this paper, we employ a Gaussian Process Regr
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,Explainable AI for?Financial Forecasting,on of features that can effectively help modeling the given classification or regression task. This process is usually not trivial and it might lead to the development of handcrafted features. Within the financial domain, this step is even more complex given the general low correlation between featu
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