Results 21 to 30 of about 2,204,167 (303)
Temporal Knowledge Graph Representation Learning [PDF]
Jisuanji kexue, 2022 As a structured form of human knowledge,knowledge graphs have played a great supportive role in supporting the semantic intercommunication of massive,multi-source,heterogeneous data,and effectively support tasks such as data analysis,attracting the ...
XU Yong-xin, ZHAO Jun-feng, WANG Ya-sha, XIE Bing, YANG Kai
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Hebbian Continual Representation Learning
Proceedings of the Annual Hawaii International Conference on System Sciences, 2023 Continual Learning aims to bring machine learning into a more realistic scenario, where tasks are learned sequentially and the i.i.d. assumption is not preserved. Although this setting is natural for biological systems, it proves very difficult for machine learning models such as artificial neural networks.
Morawiecki, Pawel +3 more
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Unnes Journal of Mathematics Education, 2023 This study aims to analyze whether the Cooperative Learning type of Reciprocal Peer Tutoring (RPT) is effective in enhancing students' mathematical representation abilities, whether it is more effective than PBL in enhancing students' mathematical ...
Fifi Suryani, Mashuri Mashuri
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A Manifold Learning Perspective on Representation Learning: Learning Decoder and Representations without an Encoder [PDF]
Entropy, 2021 Autoencoders are commonly used in representation learning. They consist of an encoder and a decoder, which provide a straightforward method to map n-dimensional data in input space to a lower m-dimensional representation space and back. The decoder itself defines an m-dimensional manifold in input space.
Viktoria Schuster, Anders Krogh
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Triplet Loss Network for Unsupervised Domain Adaptation
Algorithms, 2019 Domain adaptation is a sub-field of transfer learning that aims at bridging the dissimilarity gap between different domains by transferring and re-using the knowledge obtained in the source domain to the target domain.
Imad Eddine Ibrahim Bekkouch +4 more
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Analysis of David Kolb's Learning Style According to Mathematical Representation Ability
Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang, 2021 The purpose of this study was to describe David Kolb's learning style according to the mathematical representation of students. This research is qualitative. The subjects of this study were students of class VIII SMP Agus Salim Semarang.
Umi Hajaro +2 more
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Improving Distributed Representations of Tweets - Present and Future [PDF]
, 1915 Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking.
J, Ganesh
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A Review of Disentangled Representation Learning for Remote Sensing Data
CAAI Artificial Intelligence Research, 2022 Representation learning is one of the core problems in machine learning research. The transition of input representations for machine learning algorithms from handcraft features, which dominated in the past, to the potential representations learned ...
Mi Wang +3 more
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Multi-Task Network Representation Learning
Frontiers in Neuroscience, 2020 Networks, such as social networks, biochemical networks, and protein-protein interaction networks are ubiquitous in the real world. Network representation learning aims to embed nodes in a network as low-dimensional, dense, real-valued vectors, and ...
Yu Xie +4 more
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Modeling Relation Paths for Representation Learning of Knowledge Bases [PDF]
, 2015 Representation learning of knowledge bases (KBs) aims to embed both entities and relations into a low-dimensional space. Most existing methods only consider direct relations in representation learning.
Lin, Yankai +5 more
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