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Outlier Detection with Nonlinear Projection Pursuit
2012
International Journal of Computers Communications & Control
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The novelty of our approach resides in introducing nonlinear combinations, able to model more complex interactions among attributes. ...
Projection pursuit is basically a method to deliver meaningful linear combinations of attributes. ...
As a second test case we are interested in the ability of our method to detect the outliers when noise attributes are introduced. ...
doi:10.15837/ijccc.2013.1.165
fatcat:nfpy45so3vdu3k7kf3jucfzurm
Multi-scale Anomaly Detection on Attributed Networks
[article]
2019
arXiv
pre-print
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Besides, we introduce a graph signal processing formulation of the Markov stability framework used in community detection, in order to find the context of anomalies. ...
While some methods have proposed to spot anomalies locally, globally or within a community context, the problem remain challenging due to the multi-scale composition of real networks and the heterogeneity ...
The second one, into which our method falls, aims to detect anomalous nodes regarding the attributes of nodes within a given local context, i.e community of a node or attribute subspace. ...
arXiv:1912.04144v1
fatcat:kdanir3g6jezda3np5ui7j6onm
Multi-Scale Anomaly Detection on Attributed Networks
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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Besides, we introduce a graph signal processing formulation of the Markov stability framework used in community detection, in order to find the context of anomalies. ...
While some methods have proposed to spot anomalies locally, globally or within a community context, the problem remain challenging due to the multi-scale composition of real networks and the heterogeneity ...
The second one, into which our method falls, aims to detect anomalous nodes regarding the attributes of nodes within a given local context, i.e community of a node or attribute subspace. ...
doi:10.1609/aaai.v34i01.5409
fatcat:mwsfpiuv2rfofetqcesnko2izq
A Non-Parametric Subspace Analysis Approach with Application to Anomaly Detection Ensembles
[article]
2021
arXiv
pre-print
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Finally, the set of subspaces is used in an ensemble for anomaly detection. ...
, and (ii) generates fewer subspaces with a fewer number of attributes each (on average), thus resulting in a faster training time for the anomaly detection ensemble. ...
The y-axis represents the runtime in seconds (on a logarithmic scale), whereas the x-axis represents the theoretical complexity of the algorithm (on a logarithmic scale). ...
arXiv:2101.04932v1
fatcat:tvs46nzb5vb7xjdbqiqsv4ohxu
Multi-scale View Reveals Easily Detectable Community in Complex Networks
2019
Ingénierie des Systèmes d'Information
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Firstly, a typical multi-scale method was adopted to detect the communities in synthetic and real-world networks. ...
Then, five singlescale methods were employed for community detection in the same networks. The detection results of both types of methods were analyzed in details. ...
ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation of China (Grant number: 61806007), the National Language Committee scientific research projects of China under (Grant number ...
doi:10.18280/isi.240304
fatcat:suy5c6xpijaz3alkocuccklpdm
Plant-wide Process Monitoring Strategy based on Complex Network and Bayesian Inference-based Multi-block Principal Component Analysis
2020
IEEE Access
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In multi-block process monitoring, MBSPCA detection results are also better than MBPCA algorithm. ...
In step fault (except for failure 3), failure detection rates above 0.85 can be obtained in all multi-block process monitoring. ...
doi:10.1109/access.2020.3032597
fatcat:7ghvvccl6fel7hox2bwvaqhgcq
Introduction to the Issue on Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications
2018
IEEE Journal on Selected Topics in Signal Processing
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For abrupt changes in
the data, Jiao et al. design a subspace change-point detection
where a stream of high-dimensional data points lie on a low-
dimensional subspace. ...
His research interests consist mainly in the detection of moving objects in challenging environments. ...
doi:10.1109/jstsp.2018.2879245
fatcat:z3ohqdl37nat3pjo65fzsf2ady
A comprehensive survey of anomaly detection techniques for high dimensional big data
2020
Journal of Big Data
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Acknowledgements The article processing charge is funded by Swinburne University of Technology, Australia. ...
for Mixed-Attribute Dataset; PCA: Principal component analysis; PCC: Pearson correlation coefficient; PCP: Parallel coordinate plots; MDS: Multi dimensional scaling; SVM: Support vector machine; tSNE: ...
They used a bottom-up method to detect interesting anomaly subspaces and compute the outlying degree of anomalies in high-dimensional mixed-attribute data sets. ...
doi:10.1186/s40537-020-00320-x
fatcat:nrx7fnuzbvf65edoisv65by4s4
HyperDex
2012
Computer communication review
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The key insight behind HyperDex is the concept of hyperspace hashing in which objects with multiple attributes are mapped into a multidimensional hyperspace. ...
Distributed key-value stores are now a standard component of high-performance web services and cloud computing applications. ...
ACKNOWLEDGMENTS We would like to thank Pawel Loj for his contributions on cluster stop/restart, Deniz Altınbüken for her ConCoord Paxos implementation, and members of the HyperDex open source community ...
doi:10.1145/2377677.2377681
fatcat:xgnirmiyzbgohlwadb5jult3na
HyperDex
2012
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication - SIGCOMM '12
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The key insight behind HyperDex is the concept of hyperspace hashing in which objects with multiple attributes are mapped into a multidimensional hyperspace. ...
Distributed key-value stores are now a standard component of high-performance web services and cloud computing applications. ...
ACKNOWLEDGMENTS We would like to thank Pawel Loj for his contributions on cluster stop/restart, Deniz Altınbüken for her ConCoord Paxos implementation, and members of the HyperDex open source community ...
doi:10.1145/2342356.2342360
dblp:conf/sigcomm/EscrivaWS12
fatcat:wqgzwtrznrafpfal77sjkpldia
Table of Contents
2019
IEEE transactions on multimedia
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Cao, and N Saliency Detection via Multi-Scale Global Cues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .X. Lin, Z.-J. Wang, L. Ma, and X. ...
El Saddik 1778 Wireless and Mobile Multimedia Cache Less for More: Exploiting Cooperative Video Caching and Delivery in D2D Communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/tmm.2019.2923070
fatcat:n457i3iodjftrlg4ugc3vhyxke
Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval
2017
IEEE Transactions on Image Processing
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With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide ...
Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. ...
DA-SA is exactly the same as our domain-level subspace alignment method formulated in Eq.
B. Attribute Detection In this section, we evaluate our attribute-detection performance on both domains. ...
doi:10.1109/tip.2017.2745106
pmid:28858796
fatcat:dhp2a73iyvg67kk7yu5z2x6u7m
DUSC: Dimensionality Unbiased Subspace Clustering
2007
Seventh IEEE International Conference on Data Mining (ICDM 2007)
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In scenarios with many attributes or with noise, clusters are often hidden in subspaces of the data and do not show up in the full dimensional space. ...
For these applications, subspace clustering methods aim at detecting clusters in any subspace. Existing subspace clustering approaches fall prey to an effect we call dimensionality bias. ...
Acknowledgments: This research was funded in part by the cluster of excellence on Ultra-high speed Mobile Information and Communication (UMIC) of the DFG (German Research Foundation grant EXC 89). ...
doi:10.1109/icdm.2007.49
dblp:conf/icdm/AssentKMS07
fatcat:xpcpscejrjbpzazkrgannqyl6q
VCIP 2020 Index
2020
2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)
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Jay
Point Cloud Attribute Compression via
Successive Subspace Graph Transform
Kuo, Chung-ting
Application of Brain-Computer Interface and
Virtual Reality in Advancing Cultural Experienc
Kwan, Hon ...
Sun, Heming
Fully Neural Network Mode Based Intra
Prediction of Variable Block Size
Sun, Jun
Fast Video Saliency Detection based on Featu
Competition
Sun, Songlin
Multi-Scale Video Inverse Tone ...
doi:10.1109/vcip49819.2020.9301896
fatcat:bdh7cuvstzgrbaztnahjdp5s5y
A flabellate overlay network for multi-attribute search
2011
Journal of Parallel and Distributed Computing
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In FAN, the resources are mapped into a multi-dimensional Cartesian space based on the consistent hash values of the resource attributes. ...
Peer-to-peer (P2P) technology provides a popular way of distributing resources, sharing, and locating in a large-scale distributed environment. ...
Acknowledgments This work is supported in part by National Natural Science ...
doi:10.1016/j.jpdc.2010.11.002
fatcat:qa7r7bjqrrfqvbkujywy6vmaz4
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