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Titlebook: Artificial Intelligence; First CCF Internatio Zhi-Hua Zhou,Qiang Yang,Yu Zheng Conference proceedings 2018 Springer Nature Singapore Pte Lt

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Unsupervised Maximum Margin Incomplete Multi-view Clusteringin between different classes is enlarged in the learned subspace, leading to improvement in the clustering performance. An alternating iterative algorithm with guaranteed convergence is developed for optimization. Experimental results on several datasets verify the effectiveness of the proposed method.
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E. Grün,H. Kochan,K. Roessler,D. Stöfflere subgraphs in these areas from a set of candidate graphs to derive a safe graph, which remains to be a convex problem. Experimental results on a number of datasets show that our proposal is able to effectively avoid performance degeneration compared with many graph-based SSL methods.
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Basic Operational Amplifier Applications,menting full automation. Experimental results show that DOHM achieves the highest average accuracy ratio among the six detection methods. Moreover, DOHM makes a good balance between False Alarm Rate (FAR) and Miss Rate (MR).
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Intermediate Language: Digging Deeper,kernel formulation. By integrating the warping path information between the input time series and the centers of kernel, DBAK based RBF network (DBAK-RBF) can efficiently work for TSC tasks. Experimental results demonstrate that DBAK-RBF can achieve the better performance than previous models on benchmark time series datasets.
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Automatic Cloud Detection Based on Deep Learning from AVHRR Datamenting full automation. Experimental results show that DOHM achieves the highest average accuracy ratio among the six detection methods. Moreover, DOHM makes a good balance between False Alarm Rate (FAR) and Miss Rate (MR).
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