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You searched for subject:(Data reduction). Showing records 1 – 30 of 287 total matches.

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1. Dhungana, Prakash. Application for quick reduction of GPS data for urban mobility analysis.

Degree: 2014, Escola Superior Tecnologia e Gestão de Oliveira do Hospital

The potential requirement of using data reduction application as an assistive tool for the student and researchers has been designed, developed and deployed. For that,… (more)

Subjects/Keywords: Data analysis; Data reduction

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

APA (6th Edition):

Dhungana, P. (2014). Application for quick reduction of GPS data for urban mobility analysis. (Thesis). Escola Superior Tecnologia e Gestão de Oliveira do Hospital. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

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):

Dhungana, Prakash. “Application for quick reduction of GPS data for urban mobility analysis.” 2014. Thesis, Escola Superior Tecnologia e Gestão de Oliveira do Hospital. Accessed March 31, 2020. https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521.

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

MLA Handbook (7th Edition):

Dhungana, Prakash. “Application for quick reduction of GPS data for urban mobility analysis.” 2014. Web. 31 Mar 2020.

Vancouver:

Dhungana P. Application for quick reduction of GPS data for urban mobility analysis. [Internet] [Thesis]. Escola Superior Tecnologia e Gestão de Oliveira do Hospital; 2014. [cited 2020 Mar 31]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521.

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

Council of Science Editors:

Dhungana P. Application for quick reduction of GPS data for urban mobility analysis. [Thesis]. Escola Superior Tecnologia e Gestão de Oliveira do Hospital; 2014. Available from: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

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


Clemson University

2. Knoll, Fiona. Johnson-Lindenstrauss Transformations.

Degree: PhD, Mathematical Sciences, 2017, Clemson University

 With the quick progression of technology and the increasing need to process large data, there has been an increased interest in data-dependent and data-independent dimension… (more)

Subjects/Keywords: Data; Dimension Reduction; Johnson-Lindenstrauss

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APA (6th Edition):

Knoll, F. (2017). Johnson-Lindenstrauss Transformations. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1977

Chicago Manual of Style (16th Edition):

Knoll, Fiona. “Johnson-Lindenstrauss Transformations.” 2017. Doctoral Dissertation, Clemson University. Accessed March 31, 2020. https://tigerprints.clemson.edu/all_dissertations/1977.

MLA Handbook (7th Edition):

Knoll, Fiona. “Johnson-Lindenstrauss Transformations.” 2017. Web. 31 Mar 2020.

Vancouver:

Knoll F. Johnson-Lindenstrauss Transformations. [Internet] [Doctoral dissertation]. Clemson University; 2017. [cited 2020 Mar 31]. Available from: https://tigerprints.clemson.edu/all_dissertations/1977.

Council of Science Editors:

Knoll F. Johnson-Lindenstrauss Transformations. [Doctoral Dissertation]. Clemson University; 2017. Available from: https://tigerprints.clemson.edu/all_dissertations/1977


Oregon State University

3. Kincaid, Thomas M. Estimating absence.

Degree: PhD, Statistics, 1997, Oregon State University

 The problem addressed is absence of a class of objects in a finite set of objects, which is investigated by considering absence of a species… (more)

Subjects/Keywords: Data reduction

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APA (6th Edition):

Kincaid, T. M. (1997). Estimating absence. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/34074

Chicago Manual of Style (16th Edition):

Kincaid, Thomas M. “Estimating absence.” 1997. Doctoral Dissertation, Oregon State University. Accessed March 31, 2020. http://hdl.handle.net/1957/34074.

MLA Handbook (7th Edition):

Kincaid, Thomas M. “Estimating absence.” 1997. Web. 31 Mar 2020.

Vancouver:

Kincaid TM. Estimating absence. [Internet] [Doctoral dissertation]. Oregon State University; 1997. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/1957/34074.

Council of Science Editors:

Kincaid TM. Estimating absence. [Doctoral Dissertation]. Oregon State University; 1997. Available from: http://hdl.handle.net/1957/34074


NSYSU

4. Chen, Yu-rong. Effectively Aggregating Big Data for Visualization.

Degree: Master, Information Management, 2016, NSYSU

 With the fast development of the internet technologies, data is easily generated and collected. Those data could be useful based on how the enterprise or… (more)

Subjects/Keywords: Data Discretization; Exploratory Data Analysis; Big data; Data Reduction; Data Visualization

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APA (6th Edition):

Chen, Y. (2016). Effectively Aggregating Big Data for Visualization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

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):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Thesis, NSYSU. Accessed March 31, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

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

MLA Handbook (7th Edition):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Web. 31 Mar 2020.

Vancouver:

Chen Y. Effectively Aggregating Big Data for Visualization. [Internet] [Thesis]. NSYSU; 2016. [cited 2020 Mar 31]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

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

Council of Science Editors:

Chen Y. Effectively Aggregating Big Data for Visualization. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

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


University of Alberta

5. Fedoruk, John P. Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements.

Degree: MS, Department of Mathematical and Statistical Sciences, 2016, University of Alberta

 In an increasingly data-driven society, there is a growing need to simplify high-dimensional data sets. Over the course of the past three decades, the Johnson… (more)

Subjects/Keywords: Dimensionality Reduction; High Dimensional Data; Johnson Lindenstrauss

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

APA (6th Edition):

Fedoruk, J. P. (2016). Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cm039k5065

Chicago Manual of Style (16th Edition):

Fedoruk, John P. “Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements.” 2016. Masters Thesis, University of Alberta. Accessed March 31, 2020. https://era.library.ualberta.ca/files/cm039k5065.

MLA Handbook (7th Edition):

Fedoruk, John P. “Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements.” 2016. Web. 31 Mar 2020.

Vancouver:

Fedoruk JP. Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2020 Mar 31]. Available from: https://era.library.ualberta.ca/files/cm039k5065.

Council of Science Editors:

Fedoruk JP. Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/cm039k5065


Cornell University

6. Chen, Maximillian. Dimension Reduction And Inferential Procedures For Images .

Degree: 2014, Cornell University

 High-dimensional data analysis has been a prominent topic of statistical research in recent years due to the growing presence of high-dimensional electronic data. Much of… (more)

Subjects/Keywords: imaging data; dimension reduction; hypothesis testing

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APA (6th Edition):

Chen, M. (2014). Dimension Reduction And Inferential Procedures For Images . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/37105

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):

Chen, Maximillian. “Dimension Reduction And Inferential Procedures For Images .” 2014. Thesis, Cornell University. Accessed March 31, 2020. http://hdl.handle.net/1813/37105.

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

MLA Handbook (7th Edition):

Chen, Maximillian. “Dimension Reduction And Inferential Procedures For Images .” 2014. Web. 31 Mar 2020.

Vancouver:

Chen M. Dimension Reduction And Inferential Procedures For Images . [Internet] [Thesis]. Cornell University; 2014. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/1813/37105.

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

Council of Science Editors:

Chen M. Dimension Reduction And Inferential Procedures For Images . [Thesis]. Cornell University; 2014. Available from: http://hdl.handle.net/1813/37105

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


University of Ottawa

7. Baldiwala, Aliakbar. Dimensionality Reduction for Commercial Vehicle Fleet Monitoring .

Degree: 2018, University of Ottawa

 A variety of new features have been added in the present-day vehicles like a pre-crash warning, the vehicle to vehicle communication, semi-autonomous driving systems, telematics,… (more)

Subjects/Keywords: Data reduction; Fleet Monitoring system; CAN communication system; Comprehensive data reduction; Controller area network; CAN Busload reduction; Dimensionality reductioin

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

APA (6th Edition):

Baldiwala, A. (2018). Dimensionality Reduction for Commercial Vehicle Fleet Monitoring . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/38330

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):

Baldiwala, Aliakbar. “Dimensionality Reduction for Commercial Vehicle Fleet Monitoring .” 2018. Thesis, University of Ottawa. Accessed March 31, 2020. http://hdl.handle.net/10393/38330.

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

MLA Handbook (7th Edition):

Baldiwala, Aliakbar. “Dimensionality Reduction for Commercial Vehicle Fleet Monitoring .” 2018. Web. 31 Mar 2020.

Vancouver:

Baldiwala A. Dimensionality Reduction for Commercial Vehicle Fleet Monitoring . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/10393/38330.

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

Council of Science Editors:

Baldiwala A. Dimensionality Reduction for Commercial Vehicle Fleet Monitoring . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/38330

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


University of Johannesburg

8. Immelman, Jaco. The effect of data reduction on LiDAR-based DEMs.

Degree: 2012, University of Johannesburg

M.Sc.

Light Detection and Ranging (LiDAR) provide decidedly accurate datasets with high data densities, in a very short time-span. However, the high volumes of data(more)

Subjects/Keywords: Digital elevation models; Remote sensing - Data processing; Optical radar; Data reduction

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APA (6th Edition):

Immelman, J. (2012). The effect of data reduction on LiDAR-based DEMs. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/8064

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):

Immelman, Jaco. “The effect of data reduction on LiDAR-based DEMs.” 2012. Thesis, University of Johannesburg. Accessed March 31, 2020. http://hdl.handle.net/10210/8064.

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

MLA Handbook (7th Edition):

Immelman, Jaco. “The effect of data reduction on LiDAR-based DEMs.” 2012. Web. 31 Mar 2020.

Vancouver:

Immelman J. The effect of data reduction on LiDAR-based DEMs. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/10210/8064.

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

Council of Science Editors:

Immelman J. The effect of data reduction on LiDAR-based DEMs. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/8064

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

9. Razavi, Nasim. Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization.

Degree: MSc -MS, Computer Science, 2017, York University

Data visualization is a method to facilitate the process of knowledge discovery and decision making. Effective and practical visual analytic systems have to support real-time… (more)

Subjects/Keywords: Computer science; Interactive data visualization; Data reduction; Database systems

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APA (6th Edition):

Razavi, N. (2017). Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization. (Masters Thesis). York University. Retrieved from http://hdl.handle.net/10315/33384

Chicago Manual of Style (16th Edition):

Razavi, Nasim. “Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization.” 2017. Masters Thesis, York University. Accessed March 31, 2020. http://hdl.handle.net/10315/33384.

MLA Handbook (7th Edition):

Razavi, Nasim. “Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization.” 2017. Web. 31 Mar 2020.

Vancouver:

Razavi N. Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization. [Internet] [Masters thesis]. York University; 2017. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/10315/33384.

Council of Science Editors:

Razavi N. Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization. [Masters Thesis]. York University; 2017. Available from: http://hdl.handle.net/10315/33384

10. Bilgir Yetim, Ozlem. Minimizing Cellular Data Usage Using Application Delay Tolerance .

Degree: PhD, 2015, Princeton University

 Worldwide, mobile data usage has been increasing dramatically. As a result, users data usage costs increase. Mobile data offloading to WiFi where available could greatly… (more)

Subjects/Keywords: Cellular Data Usage Reduction; Data Offloading; Mobile Computing; WiFi Data Usage Improvement

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APA (6th Edition):

Bilgir Yetim, O. (2015). Minimizing Cellular Data Usage Using Application Delay Tolerance . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp014f16c505p

Chicago Manual of Style (16th Edition):

Bilgir Yetim, Ozlem. “Minimizing Cellular Data Usage Using Application Delay Tolerance .” 2015. Doctoral Dissertation, Princeton University. Accessed March 31, 2020. http://arks.princeton.edu/ark:/88435/dsp014f16c505p.

MLA Handbook (7th Edition):

Bilgir Yetim, Ozlem. “Minimizing Cellular Data Usage Using Application Delay Tolerance .” 2015. Web. 31 Mar 2020.

Vancouver:

Bilgir Yetim O. Minimizing Cellular Data Usage Using Application Delay Tolerance . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2020 Mar 31]. Available from: http://arks.princeton.edu/ark:/88435/dsp014f16c505p.

Council of Science Editors:

Bilgir Yetim O. Minimizing Cellular Data Usage Using Application Delay Tolerance . [Doctoral Dissertation]. Princeton University; 2015. Available from: http://arks.princeton.edu/ark:/88435/dsp014f16c505p


NSYSU

11. Ouyang, Jeng. A Similarity-based Data Reduction Approach.

Degree: Master, Electrical Engineering, 2009, NSYSU

 Finding an efficient data reduction method for large-scale problems is an imperative task. In this paper, we propose a similarity-based self-constructing fuzzy clustering algorithm to… (more)

Subjects/Keywords: fuzzy similarity; Large-scale dataset; data reduction; prototype reduction; instance-filtering; instance-abstraction

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APA (6th Edition):

Ouyang, J. (2009). A Similarity-based Data Reduction Approach. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128

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):

Ouyang, Jeng. “A Similarity-based Data Reduction Approach.” 2009. Thesis, NSYSU. Accessed March 31, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128.

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

MLA Handbook (7th Edition):

Ouyang, Jeng. “A Similarity-based Data Reduction Approach.” 2009. Web. 31 Mar 2020.

Vancouver:

Ouyang J. A Similarity-based Data Reduction Approach. [Internet] [Thesis]. NSYSU; 2009. [cited 2020 Mar 31]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128.

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

Council of Science Editors:

Ouyang J. A Similarity-based Data Reduction Approach. [Thesis]. NSYSU; 2009. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128

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


Texas State University – San Marcos

12. Reiss, Randolf H. Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression.

Degree: MS, Mathematics, 2013, Texas State University – San Marcos

 A basic theory of eigenvalues and eigenvectors as a means to reduce the dimension of data, is presented. Iterative methods for finding eigenvalues and eigenvectors… (more)

Subjects/Keywords: Eigenvector; Eigenvalue; Dimension reduction; Power method; Partial least squares; Eigenvalues; Eigenvectors; Data reduction

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APA (6th Edition):

Reiss, R. H. (2013). Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/4696

Chicago Manual of Style (16th Edition):

Reiss, Randolf H. “Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression.” 2013. Masters Thesis, Texas State University – San Marcos. Accessed March 31, 2020. https://digital.library.txstate.edu/handle/10877/4696.

MLA Handbook (7th Edition):

Reiss, Randolf H. “Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression.” 2013. Web. 31 Mar 2020.

Vancouver:

Reiss RH. Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression. [Internet] [Masters thesis]. Texas State University – San Marcos; 2013. [cited 2020 Mar 31]. Available from: https://digital.library.txstate.edu/handle/10877/4696.

Council of Science Editors:

Reiss RH. Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression. [Masters Thesis]. Texas State University – San Marcos; 2013. Available from: https://digital.library.txstate.edu/handle/10877/4696


Université Catholique de Louvain

13. Souris, Fabian. Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding.

Degree: 2015, Université Catholique de Louvain

Data visualization has always been a necessity. That is why the dimension reduction field is an important part of machine learning. One of the best… (more)

Subjects/Keywords: Nonlinear dimensionality reduction; Big Data; Data visualization; Stochastic neighbor embedding; Big Data; Data visualization; Multi scale SNE; Metric trees

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

APA (6th Edition):

Souris, F. (2015). Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:2736

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):

Souris, Fabian. “Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding.” 2015. Thesis, Université Catholique de Louvain. Accessed March 31, 2020. http://hdl.handle.net/2078.1/thesis:2736.

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

MLA Handbook (7th Edition):

Souris, Fabian. “Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding.” 2015. Web. 31 Mar 2020.

Vancouver:

Souris F. Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding. [Internet] [Thesis]. Université Catholique de Louvain; 2015. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/2078.1/thesis:2736.

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

Council of Science Editors:

Souris F. Resolution of the big-data problem related to a dimension reduction algorithm based on multi-scale similarities in stochastic neighbor embedding. [Thesis]. Université Catholique de Louvain; 2015. Available from: http://hdl.handle.net/2078.1/thesis:2736

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


RMIT University

14. Razavi Hesabi, Z. Mining complex data in highly streaming environments.

Degree: 2019, RMIT University

Data is growing at a rapid rate because of advanced hardware and software technologies and platforms such as e-health systems, sensor networks, and social media.… (more)

Subjects/Keywords: Fields of Research; data summarization; big data; machine learning; distributed computing; data management; dimensionality reduction; compression; clustering; histograms; index data structures

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APA (6th Edition):

Razavi Hesabi, Z. (2019). Mining complex data in highly streaming environments. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:162912

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):

Razavi Hesabi, Z. “Mining complex data in highly streaming environments.” 2019. Thesis, RMIT University. Accessed March 31, 2020. http://researchbank.rmit.edu.au/view/rmit:162912.

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

MLA Handbook (7th Edition):

Razavi Hesabi, Z. “Mining complex data in highly streaming environments.” 2019. Web. 31 Mar 2020.

Vancouver:

Razavi Hesabi Z. Mining complex data in highly streaming environments. [Internet] [Thesis]. RMIT University; 2019. [cited 2020 Mar 31]. Available from: http://researchbank.rmit.edu.au/view/rmit:162912.

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

Council of Science Editors:

Razavi Hesabi Z. Mining complex data in highly streaming environments. [Thesis]. RMIT University; 2019. Available from: http://researchbank.rmit.edu.au/view/rmit:162912

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


Penn State University

15. Liu, Yang. Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics.

Degree: PhD, Statistics, 2015, Penn State University

 Analysis of high-dimensional data has become increasingly important in several fields of the sciences and engineering. This is particularly true for Genomics with its expanding… (more)

Subjects/Keywords: Data integration; Genomics; Ordinary least squares; Structured data; Sufficient dimension reduction; Variable selection

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APA (6th Edition):

Liu, Y. (2015). Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26693

Chicago Manual of Style (16th Edition):

Liu, Yang. “Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics.” 2015. Doctoral Dissertation, Penn State University. Accessed March 31, 2020. https://etda.libraries.psu.edu/catalog/26693.

MLA Handbook (7th Edition):

Liu, Yang. “Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics.” 2015. Web. 31 Mar 2020.

Vancouver:

Liu Y. Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2020 Mar 31]. Available from: https://etda.libraries.psu.edu/catalog/26693.

Council of Science Editors:

Liu Y. Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics. [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26693


Penn State University

16. Laftchiev, Emil Ivanov. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.

Degree: PhD, Electrical Engineering, 2014, Penn State University

 In the modern era there is an unprecedented ability to actuate via an increasingly cheaper array of actuators, and to sense through a growing, increasingly… (more)

Subjects/Keywords: Data Dimension Reduction; Stochastic Programming; Multi-dimensional Data Representation; In-Sequence Localization

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APA (6th Edition):

Laftchiev, E. I. (2014). Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/23463

Chicago Manual of Style (16th Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Doctoral Dissertation, Penn State University. Accessed March 31, 2020. https://etda.libraries.psu.edu/catalog/23463.

MLA Handbook (7th Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Web. 31 Mar 2020.

Vancouver:

Laftchiev EI. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. [Internet] [Doctoral dissertation]. Penn State University; 2014. [cited 2020 Mar 31]. Available from: https://etda.libraries.psu.edu/catalog/23463.

Council of Science Editors:

Laftchiev EI. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. [Doctoral Dissertation]. Penn State University; 2014. Available from: https://etda.libraries.psu.edu/catalog/23463


University of Melbourne

17. 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

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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 March 31, 2020. http://hdl.handle.net/11343/58256.

MLA Handbook (7th Edition):

MONAZAM ERFANI, SARAH. “Anomaly detection in participatory sensing networks.” 2015. Web. 31 Mar 2020.

Vancouver:

MONAZAM ERFANI S. Anomaly detection in participatory sensing networks. [Internet] [Doctoral dissertation]. University of Melbourne; 2015. [cited 2020 Mar 31]. 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


George Mason University

18. Ashley, John M. Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets .

Degree: 2013, George Mason University

 NASA satellite data products are part of the recent big data explosion. An example of this are the individual physically referenced and processed footprints of… (more)

Subjects/Keywords: Computer science; Atmospheric sciences; Statistics; Climate Change; Data Compression; Data Reduction; Quantization; Remote Sensing; Visualization

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APA (6th Edition):

Ashley, J. M. (2013). Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/8779

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):

Ashley, John M. “Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets .” 2013. Thesis, George Mason University. Accessed March 31, 2020. http://hdl.handle.net/1920/8779.

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

MLA Handbook (7th Edition):

Ashley, John M. “Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets .” 2013. Web. 31 Mar 2020.

Vancouver:

Ashley JM. Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets . [Internet] [Thesis]. George Mason University; 2013. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/1920/8779.

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

Council of Science Editors:

Ashley JM. Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets . [Thesis]. George Mason University; 2013. Available from: http://hdl.handle.net/1920/8779

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


Indian Institute of Science

19. Babu, T Ravindra. Large Data Clustering And Classification Schemes For Data Mining.

Degree: 2006, Indian Institute of Science

Data Mining deals with extracting valid, novel, easily understood by humans, potentially useful and general abstractions from large data. A data is large when number… (more)

Subjects/Keywords: Data Mining; Data Classification; Image Processing; Data Clustering; Data Compaction; Data Mining - Algorithms; Hybrid Intelligent Systems; Data Reduction; Data Representation; Hybrid Schemes; Hybrid Intelligent Methods; Computer Science

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APA (6th Edition):

Babu, T. R. (2006). Large Data Clustering And Classification Schemes For Data Mining. (Thesis). Indian Institute of Science. Retrieved from http://hdl.handle.net/2005/440

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):

Babu, T Ravindra. “Large Data Clustering And Classification Schemes For Data Mining.” 2006. Thesis, Indian Institute of Science. Accessed March 31, 2020. http://hdl.handle.net/2005/440.

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

MLA Handbook (7th Edition):

Babu, T Ravindra. “Large Data Clustering And Classification Schemes For Data Mining.” 2006. Web. 31 Mar 2020.

Vancouver:

Babu TR. Large Data Clustering And Classification Schemes For Data Mining. [Internet] [Thesis]. Indian Institute of Science; 2006. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/2005/440.

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

Council of Science Editors:

Babu TR. Large Data Clustering And Classification Schemes For Data Mining. [Thesis]. Indian Institute of Science; 2006. Available from: http://hdl.handle.net/2005/440

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


University of Hong Kong

20. 李迎星.; Li, Yingxing. On sliced methods in dimension reduction.

Degree: M. Phil., 2005, University of Hong Kong

abstract

published_or_final_version

Statistics and Actuarial Science

Master

Master of Philosophy

Subjects/Keywords: Data reduction.; Regression analysis.

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

APA (6th Edition):

李迎星.; Li, Y. (2005). On sliced methods in dimension reduction. (Masters Thesis). University of Hong Kong. Retrieved from Li, Y. [李迎星]. (2005). On sliced methods in dimension reduction. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3155925 ; http://dx.doi.org/10.5353/th_b3155925 ; http://hdl.handle.net/10722/40143

Chicago Manual of Style (16th Edition):

李迎星.; Li, Yingxing. “On sliced methods in dimension reduction.” 2005. Masters Thesis, University of Hong Kong. Accessed March 31, 2020. Li, Y. [李迎星]. (2005). On sliced methods in dimension reduction. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3155925 ; http://dx.doi.org/10.5353/th_b3155925 ; http://hdl.handle.net/10722/40143.

MLA Handbook (7th Edition):

李迎星.; Li, Yingxing. “On sliced methods in dimension reduction.” 2005. Web. 31 Mar 2020.

Vancouver:

李迎星.; Li Y. On sliced methods in dimension reduction. [Internet] [Masters thesis]. University of Hong Kong; 2005. [cited 2020 Mar 31]. Available from: Li, Y. [李迎星]. (2005). On sliced methods in dimension reduction. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3155925 ; http://dx.doi.org/10.5353/th_b3155925 ; http://hdl.handle.net/10722/40143.

Council of Science Editors:

李迎星.; Li Y. On sliced methods in dimension reduction. [Masters Thesis]. University of Hong Kong; 2005. Available from: Li, Y. [李迎星]. (2005). On sliced methods in dimension reduction. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3155925 ; http://dx.doi.org/10.5353/th_b3155925 ; http://hdl.handle.net/10722/40143


University of Johannesburg

21. Visser, Hendrik Marthinus. The neural modelling of a direct reduction process.

Degree: 2014, University of Johannesburg

M.Ing. (Mechanical)

The goal of this study was to determine whether a SLIRN direct reduction process could be modelled with a neural network. The full… (more)

Subjects/Keywords: Direct reduction (Metallurgy) - Data processing; Iron - Metallurgy; Neural networks (Computer science)

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APA (6th Edition):

Visser, H. M. (2014). The neural modelling of a direct reduction process. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/11773

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):

Visser, Hendrik Marthinus. “The neural modelling of a direct reduction process.” 2014. Thesis, University of Johannesburg. Accessed March 31, 2020. http://hdl.handle.net/10210/11773.

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

MLA Handbook (7th Edition):

Visser, Hendrik Marthinus. “The neural modelling of a direct reduction process.” 2014. Web. 31 Mar 2020.

Vancouver:

Visser HM. The neural modelling of a direct reduction process. [Internet] [Thesis]. University of Johannesburg; 2014. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/10210/11773.

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

Council of Science Editors:

Visser HM. The neural modelling of a direct reduction process. [Thesis]. University of Johannesburg; 2014. Available from: http://hdl.handle.net/10210/11773

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


Rochester Institute of Technology

22. Johnson, Juan Emmanuel. Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images.

Degree: MS, School of Mathematical Sciences (COS), 2016, Rochester Institute of Technology

  Multimodal remote sensing is an upcoming field as it allows for many views of the same region of interest. Domain adaption attempts to fuse… (more)

Subjects/Keywords: Computer vision; Data fusion; Dimension reduction; Image science; Remote sensing

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APA (6th Edition):

Johnson, J. E. (2016). Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9324

Chicago Manual of Style (16th Edition):

Johnson, Juan Emmanuel. “Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed March 31, 2020. https://scholarworks.rit.edu/theses/9324.

MLA Handbook (7th Edition):

Johnson, Juan Emmanuel. “Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images.” 2016. Web. 31 Mar 2020.

Vancouver:

Johnson JE. Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2020 Mar 31]. Available from: https://scholarworks.rit.edu/theses/9324.

Council of Science Editors:

Johnson JE. Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images. [Masters Thesis]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/9324


University of Cincinnati

23. Zhou, Xuan. An Efficient Algorithm for Clustering Genomic Data.

Degree: MS, Engineering and Applied Science: Computer Science, 2014, University of Cincinnati

 In this thesis, we investigated an efficient framework for clustering analysis of gene expression profiles by discretizing continuous genomic data and adopting the 1D-jury approach… (more)

Subjects/Keywords: Computer Science; genomic data; clustering; discretization; 1D-Jury; dimension reduction

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APA (6th Edition):

Zhou, X. (2014). An Efficient Algorithm for Clustering Genomic Data. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1418910389

Chicago Manual of Style (16th Edition):

Zhou, Xuan. “An Efficient Algorithm for Clustering Genomic Data.” 2014. Masters Thesis, University of Cincinnati. Accessed March 31, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1418910389.

MLA Handbook (7th Edition):

Zhou, Xuan. “An Efficient Algorithm for Clustering Genomic Data.” 2014. Web. 31 Mar 2020.

Vancouver:

Zhou X. An Efficient Algorithm for Clustering Genomic Data. [Internet] [Masters thesis]. University of Cincinnati; 2014. [cited 2020 Mar 31]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1418910389.

Council of Science Editors:

Zhou X. An Efficient Algorithm for Clustering Genomic Data. [Masters Thesis]. University of Cincinnati; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1418910389


University of Southern California

24. Khair, Joseph Daniel. Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency.

Degree: PhD, Astronautical Engineering, 2013, University of Southern California

 Communication requirements and demands on deployed systems are increasing daily. This increase is due to the desire for more capability, but also, due to the… (more)

Subjects/Keywords: model; bandwidth; data; algorithm; reduction; transmission; model-based; ACMBT

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APA (6th Edition):

Khair, J. D. (2013). Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344419/rec/5460

Chicago Manual of Style (16th Edition):

Khair, Joseph Daniel. “Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency.” 2013. Doctoral Dissertation, University of Southern California. Accessed March 31, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344419/rec/5460.

MLA Handbook (7th Edition):

Khair, Joseph Daniel. “Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency.” 2013. Web. 31 Mar 2020.

Vancouver:

Khair JD. Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2020 Mar 31]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344419/rec/5460.

Council of Science Editors:

Khair JD. Reduction of large set data transmission using algorithmically corrected model-based techniques for bandwidth efficiency. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344419/rec/5460


University of Newcastle

25. Shaw, Peter E. Advances in cluster editing: linear FPT kernels and comparative implementations.

Degree: PhD, 2010, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

Experience has shown that clustering objects into groups is a useful way to analyze and order information. It… (more)

Subjects/Keywords: combinatorial problems; data reduction; preprocessing; computational biology; fixed-parameter tractability

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APA (6th Edition):

Shaw, P. E. (2010). Advances in cluster editing: linear FPT kernels and comparative implementations. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/928253

Chicago Manual of Style (16th Edition):

Shaw, Peter E. “Advances in cluster editing: linear FPT kernels and comparative implementations.” 2010. Doctoral Dissertation, University of Newcastle. Accessed March 31, 2020. http://hdl.handle.net/1959.13/928253.

MLA Handbook (7th Edition):

Shaw, Peter E. “Advances in cluster editing: linear FPT kernels and comparative implementations.” 2010. Web. 31 Mar 2020.

Vancouver:

Shaw PE. Advances in cluster editing: linear FPT kernels and comparative implementations. [Internet] [Doctoral dissertation]. University of Newcastle; 2010. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/1959.13/928253.

Council of Science Editors:

Shaw PE. Advances in cluster editing: linear FPT kernels and comparative implementations. [Doctoral Dissertation]. University of Newcastle; 2010. Available from: http://hdl.handle.net/1959.13/928253


Drexel University

26. DeCelles, Salvador Isaiah. Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems.

Degree: 2018, Drexel University

 Vigilance and maintenance are crucial elements toward the continued performance of any computing system. In datacenters, decisions such as resource allocation and fault detection are… (more)

Subjects/Keywords: Electrical engineering; Computer engineering; Compressed sensing (Telecommunication); Data reduction – Computer programs

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APA (6th Edition):

DeCelles, S. I. (2018). Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems. (Thesis). Drexel University. Retrieved from https://idea.library.drexel.edu/islandora/object/idea%3A8252

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):

DeCelles, Salvador Isaiah. “Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems.” 2018. Thesis, Drexel University. Accessed March 31, 2020. https://idea.library.drexel.edu/islandora/object/idea%3A8252.

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

MLA Handbook (7th Edition):

DeCelles, Salvador Isaiah. “Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems.” 2018. Web. 31 Mar 2020.

Vancouver:

DeCelles SI. Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems. [Internet] [Thesis]. Drexel University; 2018. [cited 2020 Mar 31]. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A8252.

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

Council of Science Editors:

DeCelles SI. Data Reduction Techniques for Efficient Performance Monitoring of Computing Systems. [Thesis]. Drexel University; 2018. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A8252

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


University of Arizona

27. ENGLE, MOLLY ANN. FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA.

Degree: 1983, University of Arizona

 Narrative data enable evaluators to understand other people's viewpoints without predetermining those viewpoints by using preselected questionnaire categories. Narrative data yield rich detail, insight, and… (more)

Subjects/Keywords: Data reduction.; Statistics.; Psychometrics.

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APA (6th Edition):

ENGLE, M. A. (1983). FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/187594

Chicago Manual of Style (16th Edition):

ENGLE, MOLLY ANN. “FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA. ” 1983. Doctoral Dissertation, University of Arizona. Accessed March 31, 2020. http://hdl.handle.net/10150/187594.

MLA Handbook (7th Edition):

ENGLE, MOLLY ANN. “FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA. ” 1983. Web. 31 Mar 2020.

Vancouver:

ENGLE MA. FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA. [Internet] [Doctoral dissertation]. University of Arizona; 1983. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/10150/187594.

Council of Science Editors:

ENGLE MA. FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA. [Doctoral Dissertation]. University of Arizona; 1983. Available from: http://hdl.handle.net/10150/187594


Columbia University

28. Meng, Lu. Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts.

Degree: 2016, Columbia University

 Due to the increasing availability of massive spatio-temporal data sets, modeling high dimensional data becomes quite challenging. A large number of research questions are rooted… (more)

Subjects/Keywords: Mathematical statistics – Data processing; Dynamics; Dimension reduction (Statistics); Statistics

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APA (6th Edition):

Meng, L. (2016). Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D80Z7385

Chicago Manual of Style (16th Edition):

Meng, Lu. “Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts.” 2016. Doctoral Dissertation, Columbia University. Accessed March 31, 2020. https://doi.org/10.7916/D80Z7385.

MLA Handbook (7th Edition):

Meng, Lu. “Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts.” 2016. Web. 31 Mar 2020.

Vancouver:

Meng L. Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Mar 31]. Available from: https://doi.org/10.7916/D80Z7385.

Council of Science Editors:

Meng L. Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D80Z7385


University of Oregon

29. Huck, Kevin A., 1972-. Knowledge support for parallel performance data mining.

Degree: 2009, University of Oregon

 Parallel applications running on high-end computer systems manifest a complex combination of performance phenomena, such as communication patterns, work distributions, and computational inefficiencies. Current performance… (more)

Subjects/Keywords: Parallel performance; Data mining; Dimension reduction; Clustering; Computer science

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APA (6th Edition):

Huck, Kevin A., 1. (2009). Knowledge support for parallel performance data mining. (Thesis). University of Oregon. Retrieved from http://hdl.handle.net/1794/10087

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):

Huck, Kevin A., 1972-. “Knowledge support for parallel performance data mining.” 2009. Thesis, University of Oregon. Accessed March 31, 2020. http://hdl.handle.net/1794/10087.

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

MLA Handbook (7th Edition):

Huck, Kevin A., 1972-. “Knowledge support for parallel performance data mining.” 2009. Web. 31 Mar 2020.

Vancouver:

Huck, Kevin A. 1. Knowledge support for parallel performance data mining. [Internet] [Thesis]. University of Oregon; 2009. [cited 2020 Mar 31]. Available from: http://hdl.handle.net/1794/10087.

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

Council of Science Editors:

Huck, Kevin A. 1. Knowledge support for parallel performance data mining. [Thesis]. University of Oregon; 2009. Available from: http://hdl.handle.net/1794/10087

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


University of Tennessee – Knoxville

30. Young, Joseph Kenneth. AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS.

Degree: MS, Engineering Science, 2010, University of Tennessee – Knoxville

 The University of Tennessee Space Institute’s (UTSI) active airborne science program often requires extensive modification to its fleet of aircraft in order to meet mission… (more)

Subjects/Keywords: Flight Test; Data; Reduction; Automating; Aircaft; Engineering; Other Aerospace Engineering

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APA (6th Edition):

Young, J. K. (2010). AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/846

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):

Young, Joseph Kenneth. “AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS.” 2010. Thesis, University of Tennessee – Knoxville. Accessed March 31, 2020. https://trace.tennessee.edu/utk_gradthes/846.

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

MLA Handbook (7th Edition):

Young, Joseph Kenneth. “AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS.” 2010. Web. 31 Mar 2020.

Vancouver:

Young JK. AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS. [Internet] [Thesis]. University of Tennessee – Knoxville; 2010. [cited 2020 Mar 31]. Available from: https://trace.tennessee.edu/utk_gradthes/846.

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

Council of Science Editors:

Young JK. AUTOMATING THE DATA REDUCTION PROCESS FOR MORE EFFICIENT FLIGHT TESTS AND REDUCING THE TIME FROM DAYS TO HOURS. [Thesis]. University of Tennessee – Knoxville; 2010. Available from: https://trace.tennessee.edu/utk_gradthes/846

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

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