Data representation for CNN based internet traffic classification: a comparative study
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09459-4
Abstract: It has been well established that the Internet of Things will bring an expansion in traffic volume and types. This will bring new challenges in terms of Quality of Service (QoS) and security, requiring innovative… read more here.
Keywords: traffic; machine learning; data representation; traffic classification ... See more keywords
Structure Preserving Sparse Coding for Data Representation
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DOI: 10.1007/s11063-018-9796-6
Abstract: Sparse coding methods have shown the superiority in data representation. However, traditional sparse coding methods cannot explore the manifold structure embedded in data. To alleviate this problem, a novel method, called Structure Preserving Sparse Coding… read more here.
Keywords: preserving sparse; data representation; structure preserving; sparse coding ... See more keywords
New data on the representation of women in philosophy journals: 2004–2015
Sign Up to like & getrecommendations! Published in 2018 at "Philosophical Studies"
DOI: 10.1007/s11098-017-0919-0
Abstract: This paper presents new data on the representation of women who publish in 25 top philosophy journals as ranked by the Philosophical Gourmet Report (2015) for the years 2004, 2014, and 2015. It also provides… read more here.
Keywords: data representation; representation women; philosophy; women philosophy ... See more keywords
Nonpeaked Discriminant Analysis for Data Representation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2944869
Abstract: Of late, there are many studies on the robust discriminant analysis, which adopt L1-norm as the distance metric, but their results are not robust enough to gain universal acceptance. To overcome this problem, the authors… read more here.
Keywords: distance; discriminant analysis; nonpeaked discriminant; data representation ... See more keywords
Multiview Clustering via Proximity Learning in Latent Representation Space.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3104846
Abstract: Most existing multiview clustering methods are based on the original feature space. However, the feature redundancy and noise in the original feature space limit their clustering performance. Aiming at addressing this problem, some multiview clustering… read more here.
Keywords: representation; multiview; proximity; multiview clustering ... See more keywords
Gavel: A Fast and Easy-to-Use Plain Data Representation for Software-Defined Networks
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Network and Service Management"
DOI: 10.1109/tnsm.2019.2903440
Abstract: In software-defined networking (SDN), high-level abstractions typically offer a useful means to avoid writing network applications and policies on lower levels. However, abstractions are typically developed for a specific use case, which in turn results… read more here.
Keywords: plain data; software defined; data representation; use ... See more keywords
Data Representation via Attribute Selection- Propagation Neural Network
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Signal and Information Processing over Networks"
DOI: 10.1109/tsipn.2023.3266949
Abstract: Graph Convolutional Networks (GCNs) have been commonly studied for attribute graph data representation. It is known that the core of Graph Convolution (GC) operation is to define a specific graph propagation operation for graph node's… read more here.
Keywords: graph; attribute selection; propagation; data representation ... See more keywords
A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Visualization and Computer Graphics"
DOI: 10.1109/tvcg.2016.2620975
Abstract: The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously… read more here.
Keywords: large scale; combined eulerian; data representation; eulerian lagrangian ... See more keywords
ℓ2,1 Norm and Hessian Regularized Non-Negative Matrix Factorization with Discriminability for Data Representation
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DOI: 10.3390/app7101013
Abstract: Matrix factorization based methods have widely been used in data representation. Among them, Non-negative Matrix Factorization (NMF) is a promising technique owing to its psychological and physiological interpretation of spontaneously occurring data. On one hand,… read more here.
Keywords: data representation; negative matrix; matrix; matrix factorization ... See more keywords
Yet Another Compact Time Series Data Representation using CBOR Templates (YACTS)
Sign Up to like & getrecommendations! Published in 2023 at "Sensors"
DOI: 10.3390/s23115124
Abstract: The Internet of Things (IoT) technology is growing rapidly, while the IoT devices are being deployed massively. However, interoperability with information systems remains a major challenge for this accelerated device deployment. Furthermore, most of the… read more here.
Keywords: cbor; time; time series; iot devices ... See more keywords