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Titlebook: Engineering of Computer-Based Systems; 8th International Co Jan Kofroň,Tiziana Margaria,Cristina Seceleanu Conference proceedings 2024 The

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21#
發(fā)表于 2025-3-26 00:51:51 | 只看該作者
22#
發(fā)表于 2025-3-26 07:37:06 | 只看該作者
23#
發(fā)表于 2025-3-26 11:18:28 | 只看該作者
The Genesis of Simulation in Dynamicsand the concept of responsible AI systems, fundamental to understand the technological, ethical and legal context of the current framework of debate and regulation of AI. The aim is to understand their dimension and their interrelation with the rest of the elements involved in the regulation and aud
24#
發(fā)表于 2025-3-26 15:59:11 | 只看該作者
https://doi.org/10.1007/978-1-4899-2067-6and’s board. After providing an overview of the related work, we describe how we train the two ML models and identify the optimal training and test datasets to avoid the problems of data under- and over-fitting. Given this train/test split, the trained RF and XGBoost models provide temperature predi
25#
發(fā)表于 2025-3-26 20:37:54 | 只看該作者
The Genetic Code and the Origin of Lifework targeting smart Internet of Things in edge systems is still an open challenge. A solution to that challenge named Python Testbed for Federated Learning Algorithms (PTB-FLA) appeared recently. This solution is written in pure Python, it supports both centralized and decentralized algorithms, and
26#
發(fā)表于 2025-3-26 21:56:44 | 只看該作者
27#
發(fā)表于 2025-3-27 02:21:41 | 只看該作者
https://doi.org/10.1007/978-3-031-14794-4s a web-based, low-code/no-code graphical modelling environment for ML and data analytics applications. On a case study from the medical domain, we solve the challenge of re-using AI/ML models that do not address data with imbalanced class by implementing ML algorithms in Python that do the re-balan
28#
發(fā)表于 2025-3-27 05:38:31 | 只看該作者
29#
發(fā)表于 2025-3-27 12:21:32 | 只看該作者
30#
發(fā)表于 2025-3-27 15:19:59 | 只看該作者
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