Titlebook: Nordic Artificial Intelligence Research and Development; 4th Symposium of the Evi Zouganeli,Anis Yazidi,Pedro Lind Conference proceedings‘‘

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书目名称Nordic Artificial Intelligence Research and Development影响因子(影响力)




书目名称Nordic Artificial Intelligence Research and Development影响因子(影响力)学科排名




书目名称Nordic Artificial Intelligence Research and Development网络公开度




书目名称Nordic Artificial Intelligence Research and Development网络公开度学科排名




书目名称Nordic Artificial Intelligence Research and Development被引频次




书目名称Nordic Artificial Intelligence Research and Development被引频次学科排名




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书目名称Nordic Artificial Intelligence Research and Development年度引用学科排名




书目名称Nordic Artificial Intelligence Research and Development读者反馈




书目名称Nordic Artificial Intelligence Research and Development读者反馈学科排名

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The Kernelized Taylor Diagramibutions. The kernelized Taylor diagram relates the maximum mean discrepancy and the kernel mean embedding in a single diagram, a construction that, to the best of our knowledge, have not been devised prior to this work. We believe that the kernelized Taylor diagram can be a valuable tool in data visualization.

bioavailability

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Simulating University Application Data for Fair Matchingsthat, e.g., take into account student preferences, gender balance, university preferences and study outcomes. More generally, it creates a benchmark for testing matching algorithms and fairness notions without revealing sensitive data.

漂浮

Conference proceedings‘‘‘‘‘‘‘‘ 2022, 2022. .The 11 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: robotics and intelligent systems; ai in cyber and digital sphere; ai in biological applications and medicine; and towards new ai methods..Th

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Improving the Usability of Tabular Data Through Data Annotation, Repair and Augmentationng values (data) issues), and . (to dynamically add meaningful columns and corresponding cell values to the dataset). An evaluation of the SINATRA approach based on datasets from a state-of-the-art benchmark shows promising results in terms of F1-measure and precision.

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嘲弄

statistics, computer science, and machine learning, with a distinctheft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well...Additional learning tools:..Contains “War Stories,” offering perspectives on how data science applies in t

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Evi Zouganeli,Athanasios Lentzaspendices on related process models..The book can be used to developnew courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines..