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Titlebook: Robust Latent Feature Learning for Incomplete Big Data; Di Wu Book 2023 The Author(s), under exclusive license to Springer Nature Singapor

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31#
發(fā)表于 2025-3-27 00:21:48 | 只看該作者
Information Extraction from?Visually Rich Documents Using Directed Weighted Graph Neural Networktation to capture relationships among various VRD components. In contrast to conventional methods relying on spatial proximity through Euclidean distance, our approach aims to enhance performance by introducing a novel representation of relationships using directed weighted graphs. The information e
32#
發(fā)表于 2025-3-27 03:54:35 | 只看該作者
33#
發(fā)表于 2025-3-27 07:49:15 | 只看該作者
34#
發(fā)表于 2025-3-27 12:45:46 | 只看該作者
35#
發(fā)表于 2025-3-27 15:11:34 | 只看該作者
36#
發(fā)表于 2025-3-27 21:28:18 | 只看該作者
37#
發(fā)表于 2025-3-27 22:11:23 | 只看該作者
,Die Werte der Aufkl?rung und die Politik von heute,?rkt, da? der Sozialdemokratie ein Kant not tut […], der aufzeigt, wo ihr scheinbarer Materialismus die h?chste und darum am leichtesten irreführende Ideologie ist, da? die Verachtung des Ideals, die Erhebung der materiellen Faktoten zu den omnipotenten M?chten der Entwicklung Selbstt?uschung ist.“
38#
發(fā)表于 2025-3-28 02:18:16 | 只看該作者
Vom neurologischen Symptom zur Diagnoset to more sophisticated levels of autonomy, expansion to other food subsystems beyond the culinary processes, and exploration of latent needs around HFI. The framework and further discussions are intended to better articulate, evaluate, and inform design and developments in HFI.
39#
發(fā)表于 2025-3-28 07:01:19 | 只看該作者
Jack M. Loomis,Roberta L. Klatzky,Marios Avraamides,Yvonne Lippa,Reginald G. Golledgeibutions studied; (c) compare these parameters for different distributions, different territories, and different time frames; (d) measure, geographical discrepancy (“minimal distance?0 between pairs of distributions synthetically; and 9e) obtain averaged values from many of these distances taken tog
40#
發(fā)表于 2025-3-28 11:03:56 | 只看該作者
How to Approach Ethics in Intelligent Decision Support Systemsl values as an underlying concept for a framework consisting in a set of rules that need to be part of any IDSS design. Applied to a decision process for candidate pre-selection (e.g. hiring), we illustrate the pitfalls that lead to biased decisions and methods for mitigation of “wrong decisions”, f
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