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Titlebook: Advanced Analytics and Learning on Temporal Data; 6th ECML PKDD Worksh Vincent Lemaire,Simon Malinowski,Georgiana Ifrim Conference proceedi

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樓主: metabolism
31#
發(fā)表于 2025-3-26 22:52:51 | 只看該作者
TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control by ministers. Its main aim, to quote the Employment Service Operational Plan for 1992–93, is ‘to help promote a competitive and efficient labour market particularly by giving positive help to unemployed people through its job placement service and other programmes and by the payments of benefits and allowances to those entitled to them’.
32#
發(fā)表于 2025-3-27 01:10:36 | 只看該作者
33#
發(fā)表于 2025-3-27 06:51:21 | 只看該作者
Cluster-Based Forecasting for Intermittent and Non-intermittent Time Series parodontologie enRestauratieve tandheelkunde: Door zijn visie en bevindingen te delen met andere tandartsen hoopt de auteur bij te dragen aan het optimaal behandelen van pati?nten en tevens het langetermijneffect van behandeling te vergroten.978-90-313-6581-4
34#
發(fā)表于 2025-3-27 10:46:26 | 只看該作者
35#
發(fā)表于 2025-3-27 17:12:24 | 只看該作者
36#
發(fā)表于 2025-3-27 17:49:06 | 只看該作者
37#
發(fā)表于 2025-3-27 23:00:41 | 只看該作者
Advanced Client-Side XSLT Techniques,phenotypes. Then, the sequences of phenotypes is clustered to extract typical care trajectories. This method is experimented on real data from Greater Paris university Hospital and is compared to a direct clustering of the sequences. The results show that the outputs are more easily interpretable wi
38#
發(fā)表于 2025-3-28 04:49:30 | 只看該作者
Introduction to Server-Side XML,nsional vectors using a spiking neural network learning substrate. This allows the system to learn temporal regularities in traffic data and adapt to abrupt changes, while keeping computation efficient and fast. We evaluated the performance of TRAMESINO on real-world data against relevant state-of-t
39#
發(fā)表于 2025-3-28 09:12:43 | 只看該作者
40#
發(fā)表于 2025-3-28 13:43:31 | 只看該作者
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