Results 51 to 60 of about 1,274,940 (254)
Network representation learning based on social similarities
Frontiers in Environmental Science, 2022 Analysis of large-scale networks generally requires mapping high-dimensional network data to a low-dimensional space. We thus need to represent the node and connections accurate and effectively, and representation learning could be a promising method. In
Ziwei Mo +5 more
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Unsupervised Learning of Visual Representations using Videos
, 2015 Is strong supervision necessary for learning a good visual representation? Do we really need millions of semantically-labeled images to train a Convolutional Neural Network (CNN)?
Gupta, Abhinav, Wang, Xiaolong
core +1 more source
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-View Task-Driven Recognition in Visual Sensor Networks
, 2017 Nowadays, distributed smart cameras are deployed for a wide set of tasks in several application scenarios, ranging from object recognition, image retrieval, and forensic applications.
Liu, Liu +3 more
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Identification of Key Nodes in Complex Networks Based on Network Representation Learning
IEEE Access, 2023 Recently, some research has utilized machine learning methods to identify critical nodes in complex networks. However, existing approaches often lack a comprehensive consideration of network structural features during node feature extraction.
Heping Zhang +4 more
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Attributed Network Embedding for Learning in a Dynamic Environment
, 2018 Network embedding leverages the node proximity manifested to learn a low-dimensional node vector representation for each node in the network. The learned embeddings could advance various learning tasks such as node classification, network clustering, and
Chang, Yi +5 more
core +1 more source
Representational Distance Learning for Deep Neural Networks [PDF]
Frontiers in Computational Neuroscience, 2016 Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain.
Patrick McClure, Nikolaus Kriegeskorte
openaire +3 more sources
Ambient Sound Provides Supervision for Visual Learning
, 2016 The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds can be used as a supervisory signal for learning visual models.
Freeman, William T. +4 more
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Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
DongâWoo Shin +2 more
wiley +1 more source
Network Representation Learning Enhanced Recommendation Algorithm
IEEE Access, 2019 With the popularity of social network applications, more and more recommender systems utilize trust relationships to improve the performance of traditional recommendation algorithms.
Qiang Wang +7 more
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