Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(Outlier Detection). Showing records 1 – 30 of 106 total matches.

[1] [2] [3] [4]

Search Limiters

Last 2 Years | English Only

Levels

▼ Search Limiters


University of Sydney

1. Raghavendra, Chalapathy. Deep Learning for Anomaly Detection .

Degree: 2019, University of Sydney

 Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. Anomaly detection or outlier detection is an unsupervised… (more)

Subjects/Keywords: outlier; anomaly detection; deep autoencoder

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Raghavendra, C. (2019). Deep Learning for Anomaly Detection . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/20853

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Raghavendra, Chalapathy. “Deep Learning for Anomaly Detection .” 2019. Thesis, University of Sydney. Accessed August 25, 2019. http://hdl.handle.net/2123/20853.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Raghavendra, Chalapathy. “Deep Learning for Anomaly Detection .” 2019. Web. 25 Aug 2019.

Vancouver:

Raghavendra C. Deep Learning for Anomaly Detection . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2123/20853.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Raghavendra C. Deep Learning for Anomaly Detection . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/20853

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Sydney

2. Pang, Xiaolin. Scalable Algorithms for Outlier Detection .

Degree: 2014, University of Sydney

Outlier detection is an important problem for the data mining community as outliers often embody potentially new and valuable information. Nowadays, in the face of… (more)

Subjects/Keywords: scalable algorithms; outlier detection; parallel computing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pang, X. (2014). Scalable Algorithms for Outlier Detection . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/11743

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pang, Xiaolin. “Scalable Algorithms for Outlier Detection .” 2014. Thesis, University of Sydney. Accessed August 25, 2019. http://hdl.handle.net/2123/11743.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pang, Xiaolin. “Scalable Algorithms for Outlier Detection .” 2014. Web. 25 Aug 2019.

Vancouver:

Pang X. Scalable Algorithms for Outlier Detection . [Internet] [Thesis]. University of Sydney; 2014. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2123/11743.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pang X. Scalable Algorithms for Outlier Detection . [Thesis]. University of Sydney; 2014. Available from: http://hdl.handle.net/2123/11743

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Indian Institute of Science

3. Ranga Suri, N N R. Outlier Detection with Applications in Graph Data Mining.

Degree: 2013, Indian Institute of Science

Outlier detection is an important data mining task due to its applicability in many contemporary applications such as fraud detection and anomaly detection in networks,… (more)

Subjects/Keywords: Data Mining; Graph Data Mining; Outlier Detection; Categorical Data - Outlier Detection; Network/Graph Data - Outlier Detection; Graph Data Mining - Outlier Detection; Outliers; Rough Clustering Algorithm; Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ranga Suri, N. N. R. (2013). Outlier Detection with Applications in Graph Data Mining. (Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ernet.in/2005/3447 ; http://etd.iisc.ernet.in/abstracts/4314/G25969-Abs.pdf

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ranga Suri, N N R. “Outlier Detection with Applications in Graph Data Mining.” 2013. Thesis, Indian Institute of Science. Accessed August 25, 2019. http://etd.iisc.ernet.in/2005/3447 ; http://etd.iisc.ernet.in/abstracts/4314/G25969-Abs.pdf.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ranga Suri, N N R. “Outlier Detection with Applications in Graph Data Mining.” 2013. Web. 25 Aug 2019.

Vancouver:

Ranga Suri NNR. Outlier Detection with Applications in Graph Data Mining. [Internet] [Thesis]. Indian Institute of Science; 2013. [cited 2019 Aug 25]. Available from: http://etd.iisc.ernet.in/2005/3447 ; http://etd.iisc.ernet.in/abstracts/4314/G25969-Abs.pdf.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ranga Suri NNR. Outlier Detection with Applications in Graph Data Mining. [Thesis]. Indian Institute of Science; 2013. Available from: http://etd.iisc.ernet.in/2005/3447 ; http://etd.iisc.ernet.in/abstracts/4314/G25969-Abs.pdf

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universidade Nova

4. Madsen, Jacob Hastrup. Outlier detection for improved clustering : empirical research for unsupervised data mining.

Degree: 2018, Universidade Nova

 Many clustering algorithms are sensitive to noise disturbing the results when trying to identify and characterize clusters in data. Due to the multidimensional nature of… (more)

Subjects/Keywords: Outlier Detection; Unsupervised Learning; Clustering; Data Mining

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Madsen, J. H. (2018). Outlier detection for improved clustering : empirical research for unsupervised data mining. (Thesis). Universidade Nova. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Madsen, Jacob Hastrup. “Outlier detection for improved clustering : empirical research for unsupervised data mining.” 2018. Thesis, Universidade Nova. Accessed August 25, 2019. https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Madsen, Jacob Hastrup. “Outlier detection for improved clustering : empirical research for unsupervised data mining.” 2018. Web. 25 Aug 2019.

Vancouver:

Madsen JH. Outlier detection for improved clustering : empirical research for unsupervised data mining. [Internet] [Thesis]. Universidade Nova; 2018. [cited 2019 Aug 25]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Madsen JH. Outlier detection for improved clustering : empirical research for unsupervised data mining. [Thesis]. Universidade Nova; 2018. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

5. Gohar, Usman. Scalable Techniques for Trajectory Outlier Detection.

Degree: MS, Computer Science, 2019, University of Minnesota

 The recent improvements in tracking devices and positioning satellites have led to an increased availability of spatial data describing the movement of objects such as… (more)

Subjects/Keywords: Outlier Detection; Outliers; Time-Series; Trajectories

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gohar, U. (2019). Scalable Techniques for Trajectory Outlier Detection. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/206183

Chicago Manual of Style (16th Edition):

Gohar, Usman. “Scalable Techniques for Trajectory Outlier Detection.” 2019. Masters Thesis, University of Minnesota. Accessed August 25, 2019. http://hdl.handle.net/11299/206183.

MLA Handbook (7th Edition):

Gohar, Usman. “Scalable Techniques for Trajectory Outlier Detection.” 2019. Web. 25 Aug 2019.

Vancouver:

Gohar U. Scalable Techniques for Trajectory Outlier Detection. [Internet] [Masters thesis]. University of Minnesota; 2019. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/11299/206183.

Council of Science Editors:

Gohar U. Scalable Techniques for Trajectory Outlier Detection. [Masters Thesis]. University of Minnesota; 2019. Available from: http://hdl.handle.net/11299/206183


University of Houston

6. -4882-8205. Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis.

Degree: Chemical and Biomolecular Engineering, Department of, 2015, University of Houston

 The applicability of decline relations (empirical or analytical) in rate transient analysis (RTA) to forecast the production of an unconventional reservoir depends on the validity… (more)

Subjects/Keywords: Deconvolution; Inverse Theory; Decline Curve Analysis; Local Outlier Factor; Outlier Detection; Reservoir Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-4882-8205. (2015). Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/2015

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-4882-8205. “Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis.” 2015. Thesis, University of Houston. Accessed August 25, 2019. http://hdl.handle.net/10657/2015.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-4882-8205. “Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis.” 2015. Web. 25 Aug 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-4882-8205. Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis. [Internet] [Thesis]. University of Houston; 2015. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/10657/2015.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-4882-8205. Applications of Inverse Theory and Machine Learning in Rate/Pressure Transient Analysis. [Thesis]. University of Houston; 2015. Available from: http://hdl.handle.net/10657/2015

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation


University of Miami

7. Yessembayev, Anes. Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor.

Degree: MS, Computer Science (Arts and Sciences), 2015, University of Miami

 Aggregation of data from multiple sensor nodes is usually done by simple methods such as averaging or, more sophisticated, iterative filtering methods. However, such aggregation… (more)

Subjects/Keywords: sensor network; outlier; lof; local outlier factor; detection of outliers; secure data aggregation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yessembayev, A. (2015). Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor. (Thesis). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_theses/589

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yessembayev, Anes. “Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor.” 2015. Thesis, University of Miami. Accessed August 25, 2019. https://scholarlyrepository.miami.edu/oa_theses/589.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yessembayev, Anes. “Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor.” 2015. Web. 25 Aug 2019.

Vancouver:

Yessembayev A. Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor. [Internet] [Thesis]. University of Miami; 2015. [cited 2019 Aug 25]. Available from: https://scholarlyrepository.miami.edu/oa_theses/589.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yessembayev A. Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor. [Thesis]. University of Miami; 2015. Available from: https://scholarlyrepository.miami.edu/oa_theses/589

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Alberta

8. Foss, Andrew. High-dimensional data mining: subspace clustering, outlier detection and applications to classification.

Degree: PhD, Department of Computing Science, 2010, University of Alberta

 Data mining in high dimensionality almost inevitably faces the consequences of increasing sparsity and declining differentiation between points. This is problematic because we usually exploit… (more)

Subjects/Keywords: Subspace outlier detection; Classification; GCLUS; MAXCLUS; FASTOUT; GSEP; Error estimation; Subspace clustering; T*; SERA; Outlier detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Foss, A. (2010). High-dimensional data mining: subspace clustering, outlier detection and applications to classification. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cgx41mh985

Chicago Manual of Style (16th Edition):

Foss, Andrew. “High-dimensional data mining: subspace clustering, outlier detection and applications to classification.” 2010. Doctoral Dissertation, University of Alberta. Accessed August 25, 2019. https://era.library.ualberta.ca/files/cgx41mh985.

MLA Handbook (7th Edition):

Foss, Andrew. “High-dimensional data mining: subspace clustering, outlier detection and applications to classification.” 2010. Web. 25 Aug 2019.

Vancouver:

Foss A. High-dimensional data mining: subspace clustering, outlier detection and applications to classification. [Internet] [Doctoral dissertation]. University of Alberta; 2010. [cited 2019 Aug 25]. Available from: https://era.library.ualberta.ca/files/cgx41mh985.

Council of Science Editors:

Foss A. High-dimensional data mining: subspace clustering, outlier detection and applications to classification. [Doctoral Dissertation]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/cgx41mh985


Syracuse University

9. Huang, Huaming. Rank Based Anomaly Detection Algorithms.

Degree: PhD, Electrical Engineering and Computer Science, 2013, Syracuse University

  Anomaly or outlier detection problems are of considerable importance, arising frequently in diverse real-world applications such as finance and cyber-security. Several algorithms have been… (more)

Subjects/Keywords: abnormal subsequence detection; anomalous time series detection; anomaly detection; data mining; outlier detection; time series detection; Computer Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Huang, H. (2013). Rank Based Anomaly Detection Algorithms. (Doctoral Dissertation). Syracuse University. Retrieved from https://surface.syr.edu/eecs_etd/331

Chicago Manual of Style (16th Edition):

Huang, Huaming. “Rank Based Anomaly Detection Algorithms.” 2013. Doctoral Dissertation, Syracuse University. Accessed August 25, 2019. https://surface.syr.edu/eecs_etd/331.

MLA Handbook (7th Edition):

Huang, Huaming. “Rank Based Anomaly Detection Algorithms.” 2013. Web. 25 Aug 2019.

Vancouver:

Huang H. Rank Based Anomaly Detection Algorithms. [Internet] [Doctoral dissertation]. Syracuse University; 2013. [cited 2019 Aug 25]. Available from: https://surface.syr.edu/eecs_etd/331.

Council of Science Editors:

Huang H. Rank Based Anomaly Detection Algorithms. [Doctoral Dissertation]. Syracuse University; 2013. Available from: https://surface.syr.edu/eecs_etd/331


University of Pretoria

10. Bester, Duane. The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard.

Degree: MPH, School of Health Systems and Public Health (SHSPH), 2015, University of Pretoria

 Limited research has been conducted on inconsistencies relating to whole-body vibration (WBV) field assessments. Therefore, this study aimed to investigate a certain possible contributor to… (more)

Subjects/Keywords: UCTD; Occupational hygiene; Whole-body vibration; Averaging; HavPro; Outlier detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bester, D. (2015). The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard. (Masters Thesis). University of Pretoria. Retrieved from http://hdl.handle.net/2263/46189

Chicago Manual of Style (16th Edition):

Bester, Duane. “The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard.” 2015. Masters Thesis, University of Pretoria. Accessed August 25, 2019. http://hdl.handle.net/2263/46189.

MLA Handbook (7th Edition):

Bester, Duane. “The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard.” 2015. Web. 25 Aug 2019.

Vancouver:

Bester D. The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard. [Internet] [Masters thesis]. University of Pretoria; 2015. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2263/46189.

Council of Science Editors:

Bester D. The selection of different averaging approaches on whole-body vibration exposure levels of a driver utilising the ISO 2631-1 standard. [Masters Thesis]. University of Pretoria; 2015. Available from: http://hdl.handle.net/2263/46189

11. Martinez-Camara, Marta. Blowing in the Wind: Regularizations and Outlier Removal.

Degree: 2017, EPFL

 Every day tons of pollutants are emitted into the atmosphere all around the world. These pollutants are altering the equilibrium of our planet, causing profound… (more)

Subjects/Keywords: inverse problems; regularization methods; outlier detection; emissions of pollutants; atmospheric dispersion.

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Martinez-Camara, M. (2017). Blowing in the Wind: Regularizations and Outlier Removal. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/226336

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Martinez-Camara, Marta. “Blowing in the Wind: Regularizations and Outlier Removal.” 2017. Thesis, EPFL. Accessed August 25, 2019. http://infoscience.epfl.ch/record/226336.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Martinez-Camara, Marta. “Blowing in the Wind: Regularizations and Outlier Removal.” 2017. Web. 25 Aug 2019.

Vancouver:

Martinez-Camara M. Blowing in the Wind: Regularizations and Outlier Removal. [Internet] [Thesis]. EPFL; 2017. [cited 2019 Aug 25]. Available from: http://infoscience.epfl.ch/record/226336.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Martinez-Camara M. Blowing in the Wind: Regularizations and Outlier Removal. [Thesis]. EPFL; 2017. Available from: http://infoscience.epfl.ch/record/226336

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universidade de Lisboa

12. Pais, Rui Manuel Aleixo. Detection of outliers and outliers clustering on large datasets with distributed computing.

Degree: 2012, Universidade de Lisboa

Tese de mestrado em Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2012

Outlier detection is a data analysis related problem, of… (more)

Subjects/Keywords: Outlier detection; MapReduce; Hadoop; Distributed computing; Teses de mestrado - 2012

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pais, R. M. A. (2012). Detection of outliers and outliers clustering on large datasets with distributed computing. (Thesis). Universidade de Lisboa. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ul.pt:10451/8337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pais, Rui Manuel Aleixo. “Detection of outliers and outliers clustering on large datasets with distributed computing.” 2012. Thesis, Universidade de Lisboa. Accessed August 25, 2019. http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ul.pt:10451/8337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pais, Rui Manuel Aleixo. “Detection of outliers and outliers clustering on large datasets with distributed computing.” 2012. Web. 25 Aug 2019.

Vancouver:

Pais RMA. Detection of outliers and outliers clustering on large datasets with distributed computing. [Internet] [Thesis]. Universidade de Lisboa; 2012. [cited 2019 Aug 25]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ul.pt:10451/8337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pais RMA. Detection of outliers and outliers clustering on large datasets with distributed computing. [Thesis]. Universidade de Lisboa; 2012. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ul.pt:10451/8337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – Riverside

13. Zhu, Tiantian. A Randomized Fixed Model Methodology for Genome-Wide Association Studies.

Degree: Plant Biology, 2017, University of California – Riverside

 Genome-wide association studies (GWAS) are statistical tools widely used to identify the associations between genetic variants and a quantitative trait. Through GWAS, the genetic architectures… (more)

Subjects/Keywords: Genetics; Plant sciences; GWAS; LMM; Outlier detection; RFM

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhu, T. (2017). A Randomized Fixed Model Methodology for Genome-Wide Association Studies. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/5b19953p

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhu, Tiantian. “A Randomized Fixed Model Methodology for Genome-Wide Association Studies.” 2017. Thesis, University of California – Riverside. Accessed August 25, 2019. http://www.escholarship.org/uc/item/5b19953p.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhu, Tiantian. “A Randomized Fixed Model Methodology for Genome-Wide Association Studies.” 2017. Web. 25 Aug 2019.

Vancouver:

Zhu T. A Randomized Fixed Model Methodology for Genome-Wide Association Studies. [Internet] [Thesis]. University of California – Riverside; 2017. [cited 2019 Aug 25]. Available from: http://www.escholarship.org/uc/item/5b19953p.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhu T. A Randomized Fixed Model Methodology for Genome-Wide Association Studies. [Thesis]. University of California – Riverside; 2017. Available from: http://www.escholarship.org/uc/item/5b19953p

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


UCLA

14. Tun, Jason Sopheap. Semi-Supervised Outlier Detection Algorithms.

Degree: Statistics, 2018, UCLA

 In this paper, I compared 6 semi-supervised point outlier detection algorithms: LOF, robust PCA, autoencoder, SOM, one-class SVM and isolation forest. In all experiments, I… (more)

Subjects/Keywords: Statistics; detection; LOF; One-Class; outlier; semi-supervised; SVM

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tun, J. S. (2018). Semi-Supervised Outlier Detection Algorithms. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1f03f6hb

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tun, Jason Sopheap. “Semi-Supervised Outlier Detection Algorithms.” 2018. Thesis, UCLA. Accessed August 25, 2019. http://www.escholarship.org/uc/item/1f03f6hb.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tun, Jason Sopheap. “Semi-Supervised Outlier Detection Algorithms.” 2018. Web. 25 Aug 2019.

Vancouver:

Tun JS. Semi-Supervised Outlier Detection Algorithms. [Internet] [Thesis]. UCLA; 2018. [cited 2019 Aug 25]. Available from: http://www.escholarship.org/uc/item/1f03f6hb.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tun JS. Semi-Supervised Outlier Detection Algorithms. [Thesis]. UCLA; 2018. Available from: http://www.escholarship.org/uc/item/1f03f6hb

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Université Catholique de Louvain

15. Lambot, Sue. Optimization of the REED web application for automatic outlier detection in predictive medicine.

Degree: 2017, Université Catholique de Louvain

This master thesis aims at proposing a solution to improve the current outlier detection method used by the REED online tool developed by DNAlytics and… (more)

Subjects/Keywords: machine learning; outlier detection; high dimensionality; predictive medicine; data mining

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lambot, S. (2017). Optimization of the REED web application for automatic outlier detection in predictive medicine. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:10684

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lambot, Sue. “Optimization of the REED web application for automatic outlier detection in predictive medicine.” 2017. Thesis, Université Catholique de Louvain. Accessed August 25, 2019. http://hdl.handle.net/2078.1/thesis:10684.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lambot, Sue. “Optimization of the REED web application for automatic outlier detection in predictive medicine.” 2017. Web. 25 Aug 2019.

Vancouver:

Lambot S. Optimization of the REED web application for automatic outlier detection in predictive medicine. [Internet] [Thesis]. Université Catholique de Louvain; 2017. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2078.1/thesis:10684.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lambot S. Optimization of the REED web application for automatic outlier detection in predictive medicine. [Thesis]. Université Catholique de Louvain; 2017. Available from: http://hdl.handle.net/2078.1/thesis:10684

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Virginia Tech

16. Boedihardjo, Arnold Priguna. Efficient Algorithms for Mining Data Streams.

Degree: PhD, Computer Science, 2010, Virginia Tech

 Data streams are ordered sets of values that are fast, continuous, mutable, and potentially unbounded. Examples of data streams include the pervasive time series which… (more)

Subjects/Keywords: Data Mining; Machine Learning; Kernel Density Estimation; Outlier Detection; Data Stream

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Boedihardjo, A. P. (2010). Efficient Algorithms for Mining Data Streams. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28686

Chicago Manual of Style (16th Edition):

Boedihardjo, Arnold Priguna. “Efficient Algorithms for Mining Data Streams.” 2010. Doctoral Dissertation, Virginia Tech. Accessed August 25, 2019. http://hdl.handle.net/10919/28686.

MLA Handbook (7th Edition):

Boedihardjo, Arnold Priguna. “Efficient Algorithms for Mining Data Streams.” 2010. Web. 25 Aug 2019.

Vancouver:

Boedihardjo AP. Efficient Algorithms for Mining Data Streams. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/10919/28686.

Council of Science Editors:

Boedihardjo AP. Efficient Algorithms for Mining Data Streams. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28686


Virginia Tech

17. Chen, Feng. Efficient Algorithms for Mining Large Spatio-Temporal Data.

Degree: PhD, Computer Science, 2013, Virginia Tech

 Knowledge discovery on spatio-temporal datasets has attracted growing interests. Recent advances on remote sensing technology mean that massive amounts of spatio-temporal data are being collected,… (more)

Subjects/Keywords: Spatio-Temporal Analysis; Outlier Detection; Robust Prediction; Energy Disaggregation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chen, F. (2013). Efficient Algorithms for Mining Large Spatio-Temporal Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19220

Chicago Manual of Style (16th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Doctoral Dissertation, Virginia Tech. Accessed August 25, 2019. http://hdl.handle.net/10919/19220.

MLA Handbook (7th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Web. 25 Aug 2019.

Vancouver:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/10919/19220.

Council of Science Editors:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19220


Delft University of Technology

18. Gerrits, M.R.J. Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:.

Degree: 2014, Delft University of Technology

 To obtain the absolute truth about the performance of a noise reduction method one requires to perform a listening experiment. As listening experiments are often… (more)

Subjects/Keywords: instrumental measure; kurtosis; listening experiment; outlier detection; musical noise

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gerrits, M. R. J. (2014). Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e7e6419e-877d-4874-a212-993e4fd4f568

Chicago Manual of Style (16th Edition):

Gerrits, M R J. “Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:.” 2014. Masters Thesis, Delft University of Technology. Accessed August 25, 2019. http://resolver.tudelft.nl/uuid:e7e6419e-877d-4874-a212-993e4fd4f568.

MLA Handbook (7th Edition):

Gerrits, M R J. “Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:.” 2014. Web. 25 Aug 2019.

Vancouver:

Gerrits MRJ. Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2019 Aug 25]. Available from: http://resolver.tudelft.nl/uuid:e7e6419e-877d-4874-a212-993e4fd4f568.

Council of Science Editors:

Gerrits MRJ. Evaluation of instrumental measures for the prediction of musical noise in enhanced noisy speech:. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:e7e6419e-877d-4874-a212-993e4fd4f568


University of Louisville

19. Trabelsi, Ameni. Machine learning for omics data analysis.

Degree: MS, 2018, University of Louisville

  In proteomics and metabolomics, to quantify the changes of abundance levels of biomolecules in a biological system, multiple sample analysis steps are involved. The… (more)

Subjects/Keywords: machine Learning; outlier detection; data normalization; Computer Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Trabelsi, A. (2018). Machine learning for omics data analysis. (Masters Thesis). University of Louisville. Retrieved from 10.18297/etd/2911 ; https://ir.library.louisville.edu/etd/2911

Chicago Manual of Style (16th Edition):

Trabelsi, Ameni. “Machine learning for omics data analysis.” 2018. Masters Thesis, University of Louisville. Accessed August 25, 2019. 10.18297/etd/2911 ; https://ir.library.louisville.edu/etd/2911.

MLA Handbook (7th Edition):

Trabelsi, Ameni. “Machine learning for omics data analysis.” 2018. Web. 25 Aug 2019.

Vancouver:

Trabelsi A. Machine learning for omics data analysis. [Internet] [Masters thesis]. University of Louisville; 2018. [cited 2019 Aug 25]. Available from: 10.18297/etd/2911 ; https://ir.library.louisville.edu/etd/2911.

Council of Science Editors:

Trabelsi A. Machine learning for omics data analysis. [Masters Thesis]. University of Louisville; 2018. Available from: 10.18297/etd/2911 ; https://ir.library.louisville.edu/etd/2911


ETH Zürich

20. Lucic, Mario. Computational and Statistical Tradeoffs via Data Summarization.

Degree: 2017, ETH Zürich

 The massive growth of modern datasets from different sources such as videos, social networks, and sensor data, coupled with limited resources in terms of time… (more)

Subjects/Keywords: Machine Learning; Coresets; Large-scale Machine Learning; Outlier Detection; Mixture Models

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lucic, M. (2017). Computational and Statistical Tradeoffs via Data Summarization. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/220255

Chicago Manual of Style (16th Edition):

Lucic, Mario. “Computational and Statistical Tradeoffs via Data Summarization.” 2017. Doctoral Dissertation, ETH Zürich. Accessed August 25, 2019. http://hdl.handle.net/20.500.11850/220255.

MLA Handbook (7th Edition):

Lucic, Mario. “Computational and Statistical Tradeoffs via Data Summarization.” 2017. Web. 25 Aug 2019.

Vancouver:

Lucic M. Computational and Statistical Tradeoffs via Data Summarization. [Internet] [Doctoral dissertation]. ETH Zürich; 2017. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/20.500.11850/220255.

Council of Science Editors:

Lucic M. Computational and Statistical Tradeoffs via Data Summarization. [Doctoral Dissertation]. ETH Zürich; 2017. Available from: http://hdl.handle.net/20.500.11850/220255

21. Tavares, Ana Helena Marques de Pinho. Analysis of inter genomic word distance distributions .

Degree: 2018, Universidade de Aveiro

 The investigation of DNA has been one of the most developed areas of research in this and in the last century. However, there is a… (more)

Subjects/Keywords: Genomic word distances; Distance distributions; Dissimilarity; Clustering; Outlier detection; Pattern recognition

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tavares, A. H. M. d. P. (2018). Analysis of inter genomic word distance distributions . (Thesis). Universidade de Aveiro. Retrieved from http://hdl.handle.net/10773/25792

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tavares, Ana Helena Marques de Pinho. “Analysis of inter genomic word distance distributions .” 2018. Thesis, Universidade de Aveiro. Accessed August 25, 2019. http://hdl.handle.net/10773/25792.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tavares, Ana Helena Marques de Pinho. “Analysis of inter genomic word distance distributions .” 2018. Web. 25 Aug 2019.

Vancouver:

Tavares AHMdP. Analysis of inter genomic word distance distributions . [Internet] [Thesis]. Universidade de Aveiro; 2018. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/10773/25792.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tavares AHMdP. Analysis of inter genomic word distance distributions . [Thesis]. Universidade de Aveiro; 2018. Available from: http://hdl.handle.net/10773/25792

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Australian National University

22. Zhang, Ke. Towards Outlier Detection For Scattered Data and Mixed Attribute Data .

Degree: 2010, Australian National University

 Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world knowledge discovery and data mining (KDD)… (more)

Subjects/Keywords: Outlier Detection; Scattered Data; Mixed Attribute Data; LDOF Algorithm; POD Algorithm

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, K. (2010). Towards Outlier Detection For Scattered Data and Mixed Attribute Data . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/110539

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhang, Ke. “Towards Outlier Detection For Scattered Data and Mixed Attribute Data .” 2010. Thesis, Australian National University. Accessed August 25, 2019. http://hdl.handle.net/1885/110539.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhang, Ke. “Towards Outlier Detection For Scattered Data and Mixed Attribute Data .” 2010. Web. 25 Aug 2019.

Vancouver:

Zhang K. Towards Outlier Detection For Scattered Data and Mixed Attribute Data . [Internet] [Thesis]. Australian National University; 2010. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/1885/110539.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang K. Towards Outlier Detection For Scattered Data and Mixed Attribute Data . [Thesis]. Australian National University; 2010. Available from: http://hdl.handle.net/1885/110539

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Michigan

23. Liu, Tzu-Ying. Outlier Detection for Mixed Model with Application to RNA-Seq Data.

Degree: PhD, Biostatistics, 2018, University of Michigan

 Extracting messenger RNA (mRNA) molecules using oligo-dT probes targeting on the Poly(A) tail is common in RNA-sequencing (RNA-seq) experiments. This approach, however, is limited when… (more)

Subjects/Keywords: Outlier detection; Mixed model; Statistics and Numeric Data; Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, T. (2018). Outlier Detection for Mixed Model with Application to RNA-Seq Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/147613

Chicago Manual of Style (16th Edition):

Liu, Tzu-Ying. “Outlier Detection for Mixed Model with Application to RNA-Seq Data.” 2018. Doctoral Dissertation, University of Michigan. Accessed August 25, 2019. http://hdl.handle.net/2027.42/147613.

MLA Handbook (7th Edition):

Liu, Tzu-Ying. “Outlier Detection for Mixed Model with Application to RNA-Seq Data.” 2018. Web. 25 Aug 2019.

Vancouver:

Liu T. Outlier Detection for Mixed Model with Application to RNA-Seq Data. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2027.42/147613.

Council of Science Editors:

Liu T. Outlier Detection for Mixed Model with Application to RNA-Seq Data. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/147613


University of Melbourne

24. MONAZAM ERFANI, SARAH. Anomaly detection in participatory sensing networks.

Degree: 2015, University of Melbourne

 Anomaly detection or outlier detection aims to identify unusual values in a given dataset. In particular, there is growing interest in collaborative anomaly detection, where… (more)

Subjects/Keywords: anomaly detection; outlier detection; privacy-preserving data mining; big data; random projection; dimension reduction

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

MONAZAM ERFANI, S. (2015). Anomaly detection in participatory sensing networks. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/58256

Chicago Manual of Style (16th Edition):

MONAZAM ERFANI, SARAH. “Anomaly detection in participatory sensing networks.” 2015. Doctoral Dissertation, University of Melbourne. Accessed August 25, 2019. http://hdl.handle.net/11343/58256.

MLA Handbook (7th Edition):

MONAZAM ERFANI, SARAH. “Anomaly detection in participatory sensing networks.” 2015. Web. 25 Aug 2019.

Vancouver:

MONAZAM ERFANI S. Anomaly detection in participatory sensing networks. [Internet] [Doctoral dissertation]. University of Melbourne; 2015. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/11343/58256.

Council of Science Editors:

MONAZAM ERFANI S. Anomaly detection in participatory sensing networks. [Doctoral Dissertation]. University of Melbourne; 2015. Available from: http://hdl.handle.net/11343/58256


Rochester Institute of Technology

25. Kutt, Brody. Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection.

Degree: PhD, Computer Science (GCCIS), 2018, Rochester Institute of Technology

  Autonomous streaming anomaly detection can have a significant impact in any domain where continuous, real-time data is common. Often in these domains, datasets are… (more)

Subjects/Keywords: Artificial intelligence; Hierarchical temporal memory; HOPB; Online learning; Streaming anomaly detection; Temporal outlier detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kutt, B. (2018). Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection. (Doctoral Dissertation). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9797

Chicago Manual of Style (16th Edition):

Kutt, Brody. “Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection.” 2018. Doctoral Dissertation, Rochester Institute of Technology. Accessed August 25, 2019. https://scholarworks.rit.edu/theses/9797.

MLA Handbook (7th Edition):

Kutt, Brody. “Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection.” 2018. Web. 25 Aug 2019.

Vancouver:

Kutt B. Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection. [Internet] [Doctoral dissertation]. Rochester Institute of Technology; 2018. [cited 2019 Aug 25]. Available from: https://scholarworks.rit.edu/theses/9797.

Council of Science Editors:

Kutt B. Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection. [Doctoral Dissertation]. Rochester Institute of Technology; 2018. Available from: https://scholarworks.rit.edu/theses/9797


University of Illinois – Urbana-Champaign

26. Gupta, Manish. Outlier detection for information networks.

Degree: PhD, 0112, 2013, University of Illinois – Urbana-Champaign

 The study of networks has emerged in diverse disciplines as a means of analyzing complex relationship data. There has been a significant amount of work… (more)

Subjects/Keywords: outlier detection; Community Distribution Outliers (CDOutliers); Evolutionary Community Outliers (ECOutliers); toread; data mining; outlier detection for graphs; outlier detection for networks; graph query processing; community detection; community outliers; anomalies; anomaly detection; evolution in networks

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gupta, M. (2013). Outlier detection for information networks. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/44770

Chicago Manual of Style (16th Edition):

Gupta, Manish. “Outlier detection for information networks.” 2013. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed August 25, 2019. http://hdl.handle.net/2142/44770.

MLA Handbook (7th Edition):

Gupta, Manish. “Outlier detection for information networks.” 2013. Web. 25 Aug 2019.

Vancouver:

Gupta M. Outlier detection for information networks. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2013. [cited 2019 Aug 25]. Available from: http://hdl.handle.net/2142/44770.

Council of Science Editors:

Gupta M. Outlier detection for information networks. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2013. Available from: http://hdl.handle.net/2142/44770

27. Campos, Guilherme Oliveira. Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2015, University of São Paulo

A área de detecção de outliers (ou detecção de anomalias) possui um papel fundamental na descoberta de padrões em dados que podem ser considerados excepcionais… (more)

Subjects/Keywords: Benchmark de bases de dados para detecção de outliers; Benchmark for outlier detection; Detecção não supervisionada de outliers; Evaluation measures; Métricas de avaliação; Unsupervised outlier detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Campos, G. O. (2015). Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-04082015-084412/ ;

Chicago Manual of Style (16th Edition):

Campos, Guilherme Oliveira. “Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers.” 2015. Masters Thesis, University of São Paulo. Accessed August 25, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-04082015-084412/ ;.

MLA Handbook (7th Edition):

Campos, Guilherme Oliveira. “Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers.” 2015. Web. 25 Aug 2019.

Vancouver:

Campos GO. Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers. [Internet] [Masters thesis]. University of São Paulo; 2015. [cited 2019 Aug 25]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-04082015-084412/ ;.

Council of Science Editors:

Campos GO. Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers. [Masters Thesis]. University of São Paulo; 2015. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-04082015-084412/ ;

28. Berton, Lilian. Caracterização de classes e detecção de outliers em redes complexa.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2011, University of São Paulo

As redes complexas surgiram como uma nova e importante maneira de representação e abstração de dados capaz de capturar as relações espaciais, topológicas, funcionais, entre… (more)

Subjects/Keywords: Classsificação de dados; Complex network; Data classification; Detecção de outliers; Outlier detection; Redes complexas

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Berton, L. (2011). Caracterização de classes e detecção de outliers em redes complexa. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19072011-132701/ ;

Chicago Manual of Style (16th Edition):

Berton, Lilian. “Caracterização de classes e detecção de outliers em redes complexa.” 2011. Masters Thesis, University of São Paulo. Accessed August 25, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19072011-132701/ ;.

MLA Handbook (7th Edition):

Berton, Lilian. “Caracterização de classes e detecção de outliers em redes complexa.” 2011. Web. 25 Aug 2019.

Vancouver:

Berton L. Caracterização de classes e detecção de outliers em redes complexa. [Internet] [Masters thesis]. University of São Paulo; 2011. [cited 2019 Aug 25]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19072011-132701/ ;.

Council of Science Editors:

Berton L. Caracterização de classes e detecção de outliers em redes complexa. [Masters Thesis]. University of São Paulo; 2011. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19072011-132701/ ;

29. Araújo, Bilzã Marques de. Identificação de outliers em redes complexas baseado em caminhada aleatória.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2010, University of São Paulo

Na natureza e na ciência, dados e informações que desviam significativamente da média frequentemente possuem grande relevância. Esses dados são usualmente denominados na literatura como… (more)

Subjects/Keywords: Caminhada aleatória; Complex networks; Identificação de outlies; Outlier detection; Random walk; Redes complexas

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Araújo, B. M. d. (2010). Identificação de outliers em redes complexas baseado em caminhada aleatória. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06102010-141931/ ;

Chicago Manual of Style (16th Edition):

Araújo, Bilzã Marques de. “Identificação de outliers em redes complexas baseado em caminhada aleatória.” 2010. Masters Thesis, University of São Paulo. Accessed August 25, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06102010-141931/ ;.

MLA Handbook (7th Edition):

Araújo, Bilzã Marques de. “Identificação de outliers em redes complexas baseado em caminhada aleatória.” 2010. Web. 25 Aug 2019.

Vancouver:

Araújo BMd. Identificação de outliers em redes complexas baseado em caminhada aleatória. [Internet] [Masters thesis]. University of São Paulo; 2010. [cited 2019 Aug 25]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06102010-141931/ ;.

Council of Science Editors:

Araújo BMd. Identificação de outliers em redes complexas baseado em caminhada aleatória. [Masters Thesis]. University of São Paulo; 2010. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06102010-141931/ ;


Georgia State University

30. Wang, Zhibo. Machine Learning Methods for Finding Textual Features of Depression from Publications.

Degree: PhD, Computer Science, 2017, Georgia State University

  Depression is a common but serious mood disorder. In 2015, WHO reports about 322 million people were living with some form of depression, which… (more)

Subjects/Keywords: Information retrieval; Text representation; Outlier document detection; Textual feature extraction; Word2Vec; Latent Dirichlet allocation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, Z. (2017). Machine Learning Methods for Finding Textual Features of Depression from Publications. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/cs_diss/132

Chicago Manual of Style (16th Edition):

Wang, Zhibo. “Machine Learning Methods for Finding Textual Features of Depression from Publications.” 2017. Doctoral Dissertation, Georgia State University. Accessed August 25, 2019. https://scholarworks.gsu.edu/cs_diss/132.

MLA Handbook (7th Edition):

Wang, Zhibo. “Machine Learning Methods for Finding Textual Features of Depression from Publications.” 2017. Web. 25 Aug 2019.

Vancouver:

Wang Z. Machine Learning Methods for Finding Textual Features of Depression from Publications. [Internet] [Doctoral dissertation]. Georgia State University; 2017. [cited 2019 Aug 25]. Available from: https://scholarworks.gsu.edu/cs_diss/132.

Council of Science Editors:

Wang Z. Machine Learning Methods for Finding Textual Features of Depression from Publications. [Doctoral Dissertation]. Georgia State University; 2017. Available from: https://scholarworks.gsu.edu/cs_diss/132

[1] [2] [3] [4]

.