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Titlebook: KI 2020: Advances in Artificial Intelligence; 43rd German Conferen Ute Schmid,Franziska Klügl,Diedrich Wolter Conference proceedings 2020 S

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发表于 2025-3-21 19:09:50 | 显示全部楼层 |阅读模式
书目名称KI 2020: Advances in Artificial Intelligence
副标题43rd German Conferen
编辑Ute Schmid,Franziska Klügl,Diedrich Wolter
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: KI 2020: Advances in Artificial Intelligence; 43rd German Conferen Ute Schmid,Franziska Klügl,Diedrich Wolter Conference proceedings 2020 S
描述This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020..The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions..As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. .Due to the Corona pandemic KI 2020 was held as a virtual event..
出版日期Conference proceedings 2020
关键词computer systems; computer vision; education; engineering; formal logic; image analysis; learning; linguist
版次1
doihttps://doi.org/10.1007/978-3-030-58285-2
isbn_softcover978-3-030-58284-5
isbn_ebook978-3-030-58285-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Dynamic Play via Suit Factorization Search in Skat propose mini-game solving in the . of the game, and exemplify its application as a single-dummy or double-dummy analysis tool that restricts game play to either trump or non-trump suit cards. Such factored solvers are applicable to improve card selections of the declarer and the opponents, mainly i
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Dynamic Channel and Layer Gating in Convolutional Neural Networksods for conditional computation in the context of image classification that allows a CNN to dynamically use its channels and layers conditioned on the input. To this end, we combine light-weight gating modules that can make binary decisions without causing much computational overhead. We argue, that
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Contour-Based Segmentation of Historical Printingsage layouts is still challenging, in particular, the separation of text and non-text (e.g. pictures, but also decorated initials). Fully convolutional neural nets (FCNs) with an encoder-decoder structure are currently the method of choice, if suitable training material is available. Since the variat
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Hybrid Ranking and Regression for Algorithm Selectionic instance of an algorithmic problem class. While suitability may refer to different criteria, runtime is of specific practical relevance. Leveraging empirical runtime information as training data, the AS problem is commonly tackled by fitting a regression function, which can then be used to estima
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Conditional Reasoning and Relevancemong others – the suppression task, the selection task, syllogistic reasoning, and conditional reasoning. In this paper we investigate the case where the antecedent of a conditional is true, but its consequent is unknown. We propose to apply abduction in order to find an explanation for the conseque
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Low-Rank Subspace Override for Unsupervised Domain Adaptation visual classification. Domain adaptation methods are used to improve these generalization properties. However, these techniques suffer either from being restricted to a particular task, such as visual adaptation, require a lot of computational time and data, which is not always guaranteed, have com
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