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Titlebook: Web and Big Data; 5th International Jo Leong Hou U,Marc Spaniol,Junying Chen Conference proceedings 2021 Springer Nature Switzerland AG 202

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樓主: estrange
11#
發(fā)表于 2025-3-23 11:52:44 | 只看該作者
Degree-Specific Topology Learning for Graph Convolutional Networkce; besides, we add edges between the low-degree nodes and their connectionless neighbors with high similarity in the attribute space. Experiments conducted on several popular datasets demonstrate the effectiveness of our topology learning method.
12#
發(fā)表于 2025-3-23 16:50:45 | 只看該作者
13#
發(fā)表于 2025-3-23 20:21:56 | 只看該作者
Simplifying Graph Convolutional Networks as Matrix Factorizationhe task of semi-supervised node classification, the experimental results illustrate that UCMF achieves similar or superior performances compared with GCN. Meanwhile, distributed UCMF significantly outperforms distributed GCN methods, which shows that UCMF can greatly benefit complex real-world appli
14#
發(fā)表于 2025-3-24 01:47:29 | 只看該作者
Degree-Specific Topology Learning for Graph Convolutional Networkce; besides, we add edges between the low-degree nodes and their connectionless neighbors with high similarity in the attribute space. Experiments conducted on several popular datasets demonstrate the effectiveness of our topology learning method.
15#
發(fā)表于 2025-3-24 03:45:22 | 只看該作者
Simplifying Graph Convolutional Networks as Matrix Factorizationhe task of semi-supervised node classification, the experimental results illustrate that UCMF achieves similar or superior performances compared with GCN. Meanwhile, distributed UCMF significantly outperforms distributed GCN methods, which shows that UCMF can greatly benefit complex real-world appli
16#
發(fā)表于 2025-3-24 08:21:18 | 只看該作者
Resource Trading with Hierarchical Game for Computing-Power Network Marketetwork. In this paper, we propose a computing-power market framework and formulate resource trading as a three-stage Stackelberg game. We prove the existence of Stackelberg equilibrium (SE) in game. Then the dynamic-game reinforcement learning (DG-RL) algorithm is designed to solve the optimization
17#
發(fā)表于 2025-3-24 11:59:59 | 只看該作者
Analyze and Evaluate Database-Backed Web Applications with WTool to generate configurable benchmark scripts based on collected queries. The user can use the scripts to simulate the database access of a specific application for performance evaluation. To demonstrate the usage WTool, we analyze 16 open-source web applications. We introduce several simple optimizat
18#
發(fā)表于 2025-3-24 17:59:55 | 只看該作者
19#
發(fā)表于 2025-3-24 22:25:58 | 只看該作者
Analyze and Evaluate Database-Backed Web Applications with WTool to generate configurable benchmark scripts based on collected queries. The user can use the scripts to simulate the database access of a specific application for performance evaluation. To demonstrate the usage WTool, we analyze 16 open-source web applications. We introduce several simple optimizat
20#
發(fā)表于 2025-3-25 00:30:10 | 只看該作者
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