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Titlebook: Advances in Knowledge Discovery and Data Mining; 28th Pacific-Asia Co De-Nian Yang,Xing Xie,Jerry Chun-Wei Lin Conference proceedings 2024

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41#
發(fā)表于 2025-3-28 17:53:59 | 只看該作者
Advances in Knowledge Discovery and Data Mining978-981-97-2238-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
42#
發(fā)表于 2025-3-28 19:00:48 | 只看該作者
Principles of Musculoskeletal Infectionseloped to automatize the valuation process by taking the property trading transaction into account when estimating the property value to mitigate the efforts of hand-crafted design. However, existing methods 1) only consider the real estate itself, ignoring the relation between the properties. Moreo
43#
發(fā)表于 2025-3-29 01:56:05 | 只看該作者
44#
發(fā)表于 2025-3-29 05:11:41 | 只看該作者
Ronald Peeters PhD,Stefan Sunaert MD, PhDsed on reinforcement learning (RL) have demonstrated remarkable capabilities in addressing algorithmic trading problems. However, the trading patterns differ among market conditions due to shifted distribution data. Ignoring multiple patterns in the data will undermine the performance of RL. In this
45#
發(fā)表于 2025-3-29 07:24:32 | 只看該作者
Volker M. Tronnier,Lennart H. Stieglitzlity, and the effects of algorithmic decision-making. Such insecurity has been studied within the framework of . – a concept that captures people’s latent uncertainty and precariousness. To alleviate precarity, we must study it. Precarity manifests over time as a sequence of events for an individual
46#
發(fā)表于 2025-3-29 11:43:44 | 只看該作者
47#
發(fā)表于 2025-3-29 16:06:00 | 只看該作者
GIST and Other Subepithelial Tumors, as next generation sequencing (NGS) datasets, all pair edit distance calculation based on near quadratic run time may take days or weeks. To solve this performance bottleneck problem, several sub-quadratic run time algorithms have been proposed. Recently, Pramanik et al. [.] has proposed fast refer
48#
發(fā)表于 2025-3-29 23:27:42 | 只看該作者
49#
發(fā)表于 2025-3-30 01:28:38 | 只看該作者
Mariana Temido-Ferreira,Luísa V. Lopesta unseen or partially seen in the training set. Recently, large language models (LLMs) have attracted more interests for their powers in various natural language processing tasks, but they still suffer from some issues, including less sensitivity to the order of subjects and objects and unsatisfact
50#
發(fā)表于 2025-3-30 07:02:51 | 只看該作者
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