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Titlebook: Database Systems for Advanced Applications; 28th International C Xin Wang,Maria Luisa Sapino,Hongzhi Yin Conference proceedings 2023 The Ed

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W. Lieb Nieuwoudt,Graham Moor,Rupert Baberinto the LBF, and we provide the theoretical analysis to show their lower bound property and computational efficiency. Experimental results on various synthetic and real-world datasets demonstrate the effectiveness of the proposals compared with the baseline .-means++ seeding and approximate method.
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Timothy M. Smeeding,Peter Gottschalk constraint contrastive learning (Inter-CCL) objective to effectively enlarge the discrepancy among different classes as much as possible, enforcing the strong separability for different classes in the intent embedding space. Besides, to further enhance the discriminative representation capability o
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https://doi.org/10.1007/978-1-349-26188-8rs are combined to synthesize realistically distributed data. To demonstrate the feasibility of the model, we evaluated it from three aspects: how similar are the distributions of the synthetic data to the original data, how well can the synthetic data accomplish future data mining tasks, and how mu
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International Economic Association Seriesractical rainfall interpolation well. To address these limitations, we propose a novel GSI (.raph for .patial .nterpolation) model, which focuses on learning the spatial message-passing mechanism. By constraining the message passing flow and adaptive graph structure learning, GSI can perform effecti
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The Prehistory of Chaotic Economic Dynamicss achieved by constraining the learning process with unsupervised loss functions formulated inspired by exogenous knowledge. We construct three kinds of memory modules driven by different exogenous knowledge: the long-term trend memory to learn periodic patterns, the hierarchical effect memory to ca
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https://doi.org/10.1007/978-1-349-14540-9 in the initial phase until the model is sufficiently trained and ready to use. Besides, to choose multiple actions simultaneously, we replace the actor’s output in standard reinforcement learning with a 2D matrix indicating the mixed feature representation of all different actions, then multiply it
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https://doi.org/10.1007/978-1-349-14540-9 architectures for different vulnerability detection tasks by introducing neural network architecture search (NAS) techniques. Specifically, we design a more efficient search space to ensure superior neural network architectures can be found by the search algorithm. Besides, we propose an adaptive d
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Christian Morrisson,Béchir Talbiorporate policy descriptions as external knowledge into the model. Meanwhile, a GeoEncoder is designed which encourages the model to capture unobserved background factors specified by each region and then represent them as non-text information. We evaluate the performance of a broad range of baselin
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0302-9743 for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China..The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 Ph
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