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Titlebook: Knowledge Science, Engineering and Management; 17th International C Cungeng Cao,Huajun Chen,Yonghao Wang Conference proceedings 2024 The Ed

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樓主: Coagulant
51#
發(fā)表于 2025-3-30 09:36:39 | 只看該作者
52#
發(fā)表于 2025-3-30 14:37:34 | 只看該作者
53#
發(fā)表于 2025-3-30 20:05:28 | 只看該作者
Bio-Inspired Feature Selection via?an?Improved Binary Golden Jackal Optimization Algorithmpposition-based learning, a local search strategy with feature aggregation and a global search factor with dynamic movement to enhance the performance in solving feature selection problems. Simulation experiments based on 16 classical data sets in the UC Irvine Machine Learning Repository are conduc
54#
發(fā)表于 2025-3-30 23:48:49 | 只看該作者
Dynamic Reliability-Optimised and?Energy-Efficient Scheduling Algorithms in?Heterogeneous Multi-core-OREES. To test the generality of DTRD algorithm, we also combined DTRD algorithm with the existing EFSRG algorithm as D-EFSRG algorithm. In the experimental part, the simulation scheduling results of FFT applications, GE applications and random applications show that the dynamic scheduling algorith
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發(fā)表于 2025-3-31 02:15:27 | 只看該作者
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發(fā)表于 2025-3-31 05:36:04 | 只看該作者
57#
發(fā)表于 2025-3-31 09:25:15 | 只看該作者
DVDNER: Dual-View Learning Named Entity Recognition via?Diffusionte challenges of recognizing entities in diverse contexts. (2) Rooted in a dual-view learning paradigm, DVDNER effectively merges the understanding of individual entities with their broader sentence-level contexts. This integration is key to capturing the essential contextual information for precise
58#
發(fā)表于 2025-3-31 17:05:39 | 只看該作者
Achieving Universal Fairness in?Machine Learning: A Multi-objective Optimization Perspectivehe optimal weights at rate .. Empirically, extensive experiments conducted on three real-world datasets validate that our UFair efficiently optimizes different fairness constraints alongside utility goals simultaneously.
59#
發(fā)表于 2025-3-31 17:53:23 | 只看該作者
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發(fā)表于 2025-3-31 21:52:32 | 只看該作者
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