Results 11 to 20 of about 228,260 (299)
Active Discriminative Network Representation Learning [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Most of current network representation models are learned in unsupervised fashions, which usually lack the capability of discrimination when applied to network analysis tasks, such as node classification. It is worth noting that label information is valuable for learning the discriminative network representations.
Li Gao +5 more
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Multi-modal Network Representation Learning [PDF]
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 In today's information and computational society, complex systems are often modeled as multi-modal networks associated with heterogeneous structural relation, unstructured attribute/content, temporal context, or their combinations. The abundant information in multi-modal network requires both a domain understanding and large exploratory search space ...
Chuxu Zhang +4 more
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An Optimized Network Representation Learning Algorithm Using Multi-Relational Data
Mathematics, 2019 Representation learning aims to encode the relationships of research objects into low-dimensional, compressible, and distributed representation vectors.
Zhonglin Ye +4 more
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Network Representation Learning Algorithm Based on Complete Subgraph Folding
Mathematics, 2022 Network representation learning is a machine learning method that maps network topology and node information into low-dimensional vector space. Network representation learning enables the reduction of temporal and spatial complexity in the downstream ...
Dongming Chen +4 more
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Network Representation Learning
大数据, 2015 Along with the constant growth of massive online social networks such as Facebook,Twitter,Weixin and Weibo,a tremendous amount of network data sets are generated.How to represent the data is an important aspect when we apply machine learning techniques ...
Weizheng Chen, Yan Zhang, Xiaoming Li
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Multi-View Network Representation Learning Algorithm Research
Algorithms, 2019 Network representation learning is a key research field in network data mining. In this paper, we propose a novel multi-view network representation algorithm (MVNR), which embeds multi-scale relations of network vertices into the low dimensional ...
Zhonglin Ye +3 more
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Multi-channel high-order network representation learning research [PDF]
Frontiers in NeuroroboticsThe existing network representation learning algorithms mainly model the relationship between network nodes based on the structural features of the network, or use text features, hierarchical features and other external attributes to realize the network ...
Zhonglin Ye +4 more
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Network Comparison with Interpretable Contrastive Network Representation Learning. [PDF]
J Data Sci Stat Vis, 2022 Identifying unique characteristics in a network through comparison with another network is an essential network analysis task. For example, with networks of protein interactions obtained from normal and cancer tissues, we can discover unique types of ...
Fujiwara T, Zhao J, Chen F, Yu Y, Ma KL.
europepmc +2 more sources
, 2021 Recent studies have been demonstrated that the excessive inflammatory response is an important factor of death in COVID-19 patients. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug ...
Xiaoqi W +7 more
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Heterogeneous Network Representation Learning [PDF]
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020 Representation learning has offered a revolutionary learning paradigm for various AI domains. In this survey, we examine and review the problem of representation learning with the focus on heterogeneous networks, which consists of different types of vertices and relations.
Yuxiao Dong +4 more
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