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338 total matches.

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- 2002 – 2006 (25)
- 1997 – 2001 (10)

Department

- Computer Science (12)
- Statistics (11)

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- PhD (98)
- Docteur es (29)
- MS (29)

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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

URL: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

►

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

Record Details Similar Records

❌

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

APA (6^{th} 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 (16^{th} 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 February 26, 2021. 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 (7^{th} Edition):

Dhungana, Prakash. “Application for quick reduction of GPS data for urban mobility analysis.” 2014. Web. 26 Feb 2021.

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 2021 Feb 26]. 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

Not specified: Masters Thesis or Doctoral Dissertation

Oregon State University

2. Kincaid, Thomas M. Estimating absence.

Degree: PhD, Statistics, 1997, Oregon State University

URL: http://hdl.handle.net/1957/34074

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Kincaid, Thomas M. “Estimating absence.” 1997. Doctoral Dissertation, Oregon State University. Accessed February 26, 2021. http://hdl.handle.net/1957/34074.

MLA Handbook (7^{th} Edition):

Kincaid, Thomas M. “Estimating absence.” 1997. Web. 26 Feb 2021.

Vancouver:

Kincaid TM. Estimating absence. [Internet] [Doctoral dissertation]. Oregon State University; 1997. [cited 2021 Feb 26]. 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

Clemson University

3. Knoll, Fiona. Johnson-Lindenstrauss Transformations.

Degree: PhD, Mathematical Sciences, 2017, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/1977

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Knoll, Fiona. “Johnson-Lindenstrauss Transformations.” 2017. Doctoral Dissertation, Clemson University. Accessed February 26, 2021. https://tigerprints.clemson.edu/all_dissertations/1977.

MLA Handbook (7^{th} Edition):

Knoll, Fiona. “Johnson-Lindenstrauss Transformations.” 2017. Web. 26 Feb 2021.

Vancouver:

Knoll F. Johnson-Lindenstrauss Transformations. [Internet] [Doctoral dissertation]. Clemson University; 2017. [cited 2021 Feb 26]. 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

NSYSU

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

Degree: Master, Information Management, 2016, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Thesis, NSYSU. Accessed February 26, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Web. 26 Feb 2021.

Vancouver:

Chen Y. Effectively Aggregating Big Data for Visualization. [Internet] [Thesis]. NSYSU; 2016. [cited 2021 Feb 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

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

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

URL: https://era.library.ualberta.ca/files/cm039k5065

► 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 (6^{th} 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 (16^{th} Edition):

Fedoruk, John P. “Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements.” 2016. Masters Thesis, University of Alberta. Accessed February 26, 2021. https://era.library.ualberta.ca/files/cm039k5065.

MLA Handbook (7^{th} Edition):

Fedoruk, John P. “Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements.” 2016. Web. 26 Feb 2021.

Vancouver:

Fedoruk JP. Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2021 Feb 26]. 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: PhD, Statistics, 2014, Cornell University

URL: http://hdl.handle.net/1813/37105

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Chen, Maximillian. “Dimension Reduction And Inferential Procedures For Images.” 2014. Doctoral Dissertation, Cornell University. Accessed February 26, 2021. http://hdl.handle.net/1813/37105.

MLA Handbook (7^{th} Edition):

Chen, Maximillian. “Dimension Reduction And Inferential Procedures For Images.” 2014. Web. 26 Feb 2021.

Vancouver:

Chen M. Dimension Reduction And Inferential Procedures For Images. [Internet] [Doctoral dissertation]. Cornell University; 2014. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/1813/37105.

Council of Science Editors:

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

7. ALAKKARI, SALAHEDDIN. Modelling Large-scale Datasets Using Principal Component Analysis.

Degree: School of Computer Science & Statistics. Discipline of Computer Science, 2020, Trinity College Dublin

URL: http://hdl.handle.net/2262/92525

► Principal Component Analysis (PCA) is one of the most well-known unsupervised learning techniques used for dimensionality *reduction* and feature extraction. The main task of PCA…
(more)

Subjects/Keywords: dimensionality reduction; unsupervised machine learning; data analysis

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APA (6^{th} Edition):

ALAKKARI, S. (2020). Modelling Large-scale Datasets Using Principal Component Analysis. (Thesis). Trinity College Dublin. Retrieved from http://hdl.handle.net/2262/92525

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

ALAKKARI, SALAHEDDIN. “Modelling Large-scale Datasets Using Principal Component Analysis.” 2020. Thesis, Trinity College Dublin. Accessed February 26, 2021. http://hdl.handle.net/2262/92525.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

ALAKKARI, SALAHEDDIN. “Modelling Large-scale Datasets Using Principal Component Analysis.” 2020. Web. 26 Feb 2021.

Vancouver:

ALAKKARI S. Modelling Large-scale Datasets Using Principal Component Analysis. [Internet] [Thesis]. Trinity College Dublin; 2020. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/2262/92525.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ALAKKARI S. Modelling Large-scale Datasets Using Principal Component Analysis. [Thesis]. Trinity College Dublin; 2020. Available from: http://hdl.handle.net/2262/92525

Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

8.
Krishnaraj, Manoj (author).
Comparative Analysis of Techniques for *Data* Minimization for Recommender System algorithms.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:35e19f20-6161-4755-b9a5-7714af15a840

►

Recommender systems (RS) often use a large amount of *data* for a marginal gain in performance. This thesis investigates the *data* minimization in Recommender Systems,…
(more)

Subjects/Keywords: Recommender Systems; Collaborative Filtering; Data Reduction

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APA (6^{th} Edition):

Krishnaraj, M. (. (2019). Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:35e19f20-6161-4755-b9a5-7714af15a840

Chicago Manual of Style (16^{th} Edition):

Krishnaraj, Manoj (author). “Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms.” 2019. Masters Thesis, Delft University of Technology. Accessed February 26, 2021. http://resolver.tudelft.nl/uuid:35e19f20-6161-4755-b9a5-7714af15a840.

MLA Handbook (7^{th} Edition):

Krishnaraj, Manoj (author). “Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms.” 2019. Web. 26 Feb 2021.

Vancouver:

Krishnaraj M(. Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 26]. Available from: http://resolver.tudelft.nl/uuid:35e19f20-6161-4755-b9a5-7714af15a840.

Council of Science Editors:

Krishnaraj M(. Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:35e19f20-6161-4755-b9a5-7714af15a840

University of Waterloo

9.
Xie, Yijun.
Applications of Projection Pursuit in Functional *Data* Analysis: Goodness-of- fit, Forecasting, and Change-point Detection.

Degree: 2021, University of Waterloo

URL: http://hdl.handle.net/10012/16710

► Dimension *reduction* methods for functional *data* have been avidly studied in recent years. However, existing methods are primarily based on summarizing the *data* by their…
(more)

Subjects/Keywords: functional data analysis; dimension reduction; projection pursuit

Record Details Similar Records

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

APA (6^{th} Edition):

Xie, Y. (2021). Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16710

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Xie, Yijun. “Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection.” 2021. Thesis, University of Waterloo. Accessed February 26, 2021. http://hdl.handle.net/10012/16710.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Xie, Yijun. “Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection.” 2021. Web. 26 Feb 2021.

Vancouver:

Xie Y. Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection. [Internet] [Thesis]. University of Waterloo; 2021. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10012/16710.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xie Y. Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection. [Thesis]. University of Waterloo; 2021. Available from: http://hdl.handle.net/10012/16710

Not specified: Masters Thesis or Doctoral Dissertation

University of Ottawa

10.
Baldiwala, Aliakbar.
Dimensionality *Reduction* for Commercial Vehicle Fleet Monitoring
.

Degree: 2018, University of Ottawa

URL: http://hdl.handle.net/10393/38330

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Baldiwala, Aliakbar. “Dimensionality Reduction for Commercial Vehicle Fleet Monitoring .” 2018. Thesis, University of Ottawa. Accessed February 26, 2021. http://hdl.handle.net/10393/38330.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Baldiwala, Aliakbar. “Dimensionality Reduction for Commercial Vehicle Fleet Monitoring .” 2018. Web. 26 Feb 2021.

Vancouver:

Baldiwala A. Dimensionality Reduction for Commercial Vehicle Fleet Monitoring . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10393/38330.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Johannesburg

11.
Immelman, Jaco.
The effect of *data* *reduction* on LiDAR-based DEMs.

Degree: 2012, University of Johannesburg

URL: http://hdl.handle.net/10210/8064

►

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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Immelman, Jaco. “The effect of data reduction on LiDAR-based DEMs.” 2012. Thesis, University of Johannesburg. Accessed February 26, 2021. http://hdl.handle.net/10210/8064.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Immelman, Jaco. “The effect of data reduction on LiDAR-based DEMs.” 2012. Web. 26 Feb 2021.

Vancouver:

Immelman J. The effect of data reduction on LiDAR-based DEMs. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10210/8064.

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

Not specified: Masters Thesis or Doctoral Dissertation

York University

12.
Razavi, Nasim.
Hierarchical Aggregate Structure by Inductive Aggregation for Interactive *Data* Visualization.

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

URL: http://hdl.handle.net/10315/33384

► *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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Razavi, Nasim. “Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization.” 2017. Masters Thesis, York University. Accessed February 26, 2021. http://hdl.handle.net/10315/33384.

MLA Handbook (7^{th} Edition):

Razavi, Nasim. “Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization.” 2017. Web. 26 Feb 2021.

Vancouver:

Razavi N. Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization. [Internet] [Masters thesis]. York University; 2017. [cited 2021 Feb 26]. 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

13.
Bilgir Yetim, Ozlem.
Minimizing Cellular *Data* Usage Using Application Delay Tolerance
.

Degree: PhD, 2015, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp014f16c505p

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Bilgir Yetim, Ozlem. “Minimizing Cellular Data Usage Using Application Delay Tolerance .” 2015. Doctoral Dissertation, Princeton University. Accessed February 26, 2021. http://arks.princeton.edu/ark:/88435/dsp014f16c505p.

MLA Handbook (7^{th} Edition):

Bilgir Yetim, Ozlem. “Minimizing Cellular Data Usage Using Application Delay Tolerance .” 2015. Web. 26 Feb 2021.

Vancouver:

Bilgir Yetim O. Minimizing Cellular Data Usage Using Application Delay Tolerance . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2021 Feb 26]. 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

14.
Ouyang, Jeng.
A Similarity-based *Data* *Reduction* Approach.

Degree: Master, Electrical Engineering, 2009, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ouyang, Jeng. “A Similarity-based Data Reduction Approach.” 2009. Thesis, NSYSU. Accessed February 26, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ouyang, Jeng. “A Similarity-based Data Reduction Approach.” 2009. Web. 26 Feb 2021.

Vancouver:

Ouyang J. A Similarity-based Data Reduction Approach. [Internet] [Thesis]. NSYSU; 2009. [cited 2021 Feb 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907109-164128.

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

Not specified: Masters Thesis or Doctoral Dissertation

Texas State University – San Marcos

15.
Reiss, Randolf H.
Eigenvalues and Eigenvectors in *Data* Dimension *Reduction* for Regression.

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

URL: https://digital.library.txstate.edu/handle/10877/4696

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Reiss, Randolf H. “Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression.” 2013. Masters Thesis, Texas State University – San Marcos. Accessed February 26, 2021. https://digital.library.txstate.edu/handle/10877/4696.

MLA Handbook (7^{th} Edition):

Reiss, Randolf H. “Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression.” 2013. Web. 26 Feb 2021.

Vancouver:

Reiss RH. Eigenvalues and Eigenvectors in Data Dimension Reduction for Regression. [Internet] [Masters thesis]. Texas State University – San Marcos; 2013. [cited 2021 Feb 26]. 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

RMIT University

16.
Razavi Hesabi, Z.
Mining complex *data* in highly streaming environments.

Degree: 2019, RMIT University

URL: http://researchbank.rmit.edu.au/view/rmit:162912

► *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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Razavi Hesabi, Z. “Mining complex data in highly streaming environments.” 2019. Thesis, RMIT University. Accessed February 26, 2021. http://researchbank.rmit.edu.au/view/rmit:162912.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Razavi Hesabi, Z. “Mining complex data in highly streaming environments.” 2019. Web. 26 Feb 2021.

Vancouver:

Razavi Hesabi Z. Mining complex data in highly streaming environments. [Internet] [Thesis]. RMIT University; 2019. [cited 2021 Feb 26]. Available from: http://researchbank.rmit.edu.au/view/rmit:162912.

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

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

17.
Laftchiev, Emil Ivanov.
Robust Dynamical Model-based *Data* Representations and Structuring of Time Series *Data* for In-sequence Localization.

Degree: 2014, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/23463

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Thesis, Penn State University. Accessed February 26, 2021. https://submit-etda.libraries.psu.edu/catalog/23463.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Web. 26 Feb 2021.

Vancouver:

Laftchiev EI. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Feb 26]. Available from: https://submit-etda.libraries.psu.edu/catalog/23463.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

18.
Liu, Yang.
Approaches to reduce and integrate *data* in structured and high-dimensional regression problems in Genomics.

Degree: 2015, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/26693

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Liu, Yang. “Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics.” 2015. Thesis, Penn State University. Accessed February 26, 2021. https://submit-etda.libraries.psu.edu/catalog/26693.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Liu, Yang. “Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics.” 2015. Web. 26 Feb 2021.

Vancouver:

Liu Y. Approaches to reduce and integrate data in structured and high-dimensional regression problems in Genomics. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Feb 26]. Available from: https://submit-etda.libraries.psu.edu/catalog/26693.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Not specified: Masters Thesis or Doctoral Dissertation

George Mason University

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

Degree: 2013, George Mason University

URL: http://hdl.handle.net/1920/8779

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ashley, John M. “Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets .” 2013. Thesis, George Mason University. Accessed February 26, 2021. http://hdl.handle.net/1920/8779.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ashley, John M. “Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets .” 2013. Web. 26 Feb 2021.

Vancouver:

Ashley JM. Techniques for Exploring Cluster Compressed Geospatial-Temporal Satellite Datasets . [Internet] [Thesis]. George Mason University; 2013. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/1920/8779.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Melbourne

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

Degree: 2015, University of Melbourne

URL: http://hdl.handle.net/11343/58256

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

APA (6^{th} 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 (16^{th} Edition):

MONAZAM ERFANI, SARAH. “Anomaly detection in participatory sensing networks.” 2015. Doctoral Dissertation, University of Melbourne. Accessed February 26, 2021. http://hdl.handle.net/11343/58256.

MLA Handbook (7^{th} Edition):

MONAZAM ERFANI, SARAH. “Anomaly detection in participatory sensing networks.” 2015. Web. 26 Feb 2021.

Vancouver:

MONAZAM ERFANI S. Anomaly detection in participatory sensing networks. [Internet] [Doctoral dissertation]. University of Melbourne; 2015. [cited 2021 Feb 26]. 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

University of Canterbury

21. Henley, Lisa. The quantification and visualisation of human flourishing.

Degree: PhD, Mathematics, 2015, University of Canterbury

URL: http://dx.doi.org/10.26021/2506

► Economic indicators such as GDP have been a main indicator of human progress since the first half of last century. There is concern that continuing…
(more)

Subjects/Keywords: human flourishing; genetic algorithms; spectral clustering; data visualisation; data reduction; human progress

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

APA (6^{th} Edition):

Henley, L. (2015). The quantification and visualisation of human flourishing. (Doctoral Dissertation). University of Canterbury. Retrieved from http://dx.doi.org/10.26021/2506

Chicago Manual of Style (16^{th} Edition):

Henley, Lisa. “The quantification and visualisation of human flourishing.” 2015. Doctoral Dissertation, University of Canterbury. Accessed February 26, 2021. http://dx.doi.org/10.26021/2506.

MLA Handbook (7^{th} Edition):

Henley, Lisa. “The quantification and visualisation of human flourishing.” 2015. Web. 26 Feb 2021.

Vancouver:

Henley L. The quantification and visualisation of human flourishing. [Internet] [Doctoral dissertation]. University of Canterbury; 2015. [cited 2021 Feb 26]. Available from: http://dx.doi.org/10.26021/2506.

Council of Science Editors:

Henley L. The quantification and visualisation of human flourishing. [Doctoral Dissertation]. University of Canterbury; 2015. Available from: http://dx.doi.org/10.26021/2506

22.
Landgraf, Andrew J.
Generalized Principal Component Analysis: Dimensionality
*Reduction* through the Projection of Natural Parameters.

Degree: PhD, Statistics, 2015, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1437610558

► Principal component analysis (PCA) is very useful for a wide variety of *data* analysis tasks, but its implicit connection to the Gaussian distribution can be…
(more)

Subjects/Keywords: Statistics; Binary data; Count data; Dimensionality reduction; Exponential family; Logistic PCA; Principal component analysis

Record Details Similar Records

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

APA (6^{th} Edition):

Landgraf, A. J. (2015). Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1437610558

Chicago Manual of Style (16^{th} Edition):

Landgraf, Andrew J. “Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters.” 2015. Doctoral Dissertation, The Ohio State University. Accessed February 26, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437610558.

MLA Handbook (7^{th} Edition):

Landgraf, Andrew J. “Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters.” 2015. Web. 26 Feb 2021.

Vancouver:

Landgraf AJ. Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters. [Internet] [Doctoral dissertation]. The Ohio State University; 2015. [cited 2021 Feb 26]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1437610558.

Council of Science Editors:

Landgraf AJ. Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters. [Doctoral Dissertation]. The Ohio State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1437610558

University of Newcastle

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

Degree: PhD, 2010, University of Newcastle

URL: http://hdl.handle.net/1959.13/928253

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Shaw, Peter E. “Advances in cluster editing: linear FPT kernels and comparative implementations.” 2010. Doctoral Dissertation, University of Newcastle. Accessed February 26, 2021. http://hdl.handle.net/1959.13/928253.

MLA Handbook (7^{th} Edition):

Shaw, Peter E. “Advances in cluster editing: linear FPT kernels and comparative implementations.” 2010. Web. 26 Feb 2021.

Vancouver:

Shaw PE. Advances in cluster editing: linear FPT kernels and comparative implementations. [Internet] [Doctoral dissertation]. University of Newcastle; 2010. [cited 2021 Feb 26]. 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

Rochester Institute of Technology

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

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

URL: https://scholarworks.rit.edu/theses/9324

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Johnson, Juan Emmanuel. “Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed February 26, 2021. https://scholarworks.rit.edu/theses/9324.

MLA Handbook (7^{th} Edition):

Johnson, Juan Emmanuel. “Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images.” 2016. Web. 26 Feb 2021.

Vancouver:

Johnson JE. Schroedinger Eigenmaps for Manifold Alignment of Multimodal Hyperspectral Images. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2021 Feb 26]. 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

Vanderbilt University

25. Peterson, Emily Nancy. Assessment of Propensity Score Performance in Small Samples.

Degree: MS, Biostatistics, 2015, Vanderbilt University

URL: http://hdl.handle.net/1803/13205

► BIOSTATISTICS ASSESSMENT OF PROPENSITY SCORE PERFORMANCE IN SMALL SAMPLES EMILY PETERSON Thesis under the direction of Professor Tatsuki Koyama In observational studies, treatment selection is…
(more)

Subjects/Keywords: propensity score models; small sample; simulation; data reduction

Record Details Similar Records

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

APA (6^{th} Edition):

Peterson, E. N. (2015). Assessment of Propensity Score Performance in Small Samples. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/13205

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Peterson, Emily Nancy. “Assessment of Propensity Score Performance in Small Samples.” 2015. Thesis, Vanderbilt University. Accessed February 26, 2021. http://hdl.handle.net/1803/13205.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Peterson, Emily Nancy. “Assessment of Propensity Score Performance in Small Samples.” 2015. Web. 26 Feb 2021.

Vancouver:

Peterson EN. Assessment of Propensity Score Performance in Small Samples. [Internet] [Thesis]. Vanderbilt University; 2015. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/1803/13205.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Peterson EN. Assessment of Propensity Score Performance in Small Samples. [Thesis]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/13205

Not specified: Masters Thesis or Doctoral Dissertation

Stellenbosch University

26.
Thomas, Jason Todd.
The Use of Radar *Data* to Derive Areal *Reduction* Factors for South Africa.

Degree: MEng, Civil Engineering, 2019, Stellenbosch University

URL: http://hdl.handle.net/10019.1/107071

►

ENGLISH ABSTRACT: An areal *reduction* factor (ARF) can be defined as a factor that is applied to point rainfall depths to convert these depths to…
(more)

Subjects/Keywords: Areal Reduction Factor; Hydrology; Radar – Data; Storms; UCTD

Record Details Similar Records

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

APA (6^{th} Edition):

Thomas, J. T. (2019). The Use of Radar Data to Derive Areal Reduction Factors for South Africa. (Thesis). Stellenbosch University. Retrieved from http://hdl.handle.net/10019.1/107071

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Thomas, Jason Todd. “The Use of Radar Data to Derive Areal Reduction Factors for South Africa.” 2019. Thesis, Stellenbosch University. Accessed February 26, 2021. http://hdl.handle.net/10019.1/107071.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Thomas, Jason Todd. “The Use of Radar Data to Derive Areal Reduction Factors for South Africa.” 2019. Web. 26 Feb 2021.

Vancouver:

Thomas JT. The Use of Radar Data to Derive Areal Reduction Factors for South Africa. [Internet] [Thesis]. Stellenbosch University; 2019. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10019.1/107071.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Thomas JT. The Use of Radar Data to Derive Areal Reduction Factors for South Africa. [Thesis]. Stellenbosch University; 2019. Available from: http://hdl.handle.net/10019.1/107071

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

27.
Christou, Eliana.
A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored * Data*.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/28762

► Quantile regression (QR) is becoming increasingly popular due to its relevance in many scientific investigations. Linear and nonlinear QR models have been studied extensively, while…
(more)

Subjects/Keywords: Censored Data; Dimension reduction; Index model; Nadaraya-Watson estimator; Quantile regression.

Record Details Similar Records

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

APA (6^{th} Edition):

Christou, E. (2016). A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored Data. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28762

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Christou, Eliana. “A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored Data.” 2016. Thesis, Penn State University. Accessed February 26, 2021. https://submit-etda.libraries.psu.edu/catalog/28762.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Christou, Eliana. “A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored Data.” 2016. Web. 26 Feb 2021.

Vancouver:

Christou E. A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored Data. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Feb 26]. Available from: https://submit-etda.libraries.psu.edu/catalog/28762.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Christou E. A Non-iterative Method for Fitting the Single Index Quantile Regression Model with Uncensored and Censored Data. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28762

Not specified: Masters Thesis or Doctoral Dissertation

University of Johannesburg

28.
Visser, Hendrik Marthinus.
The neural modelling of a direct *reduction* process.

Degree: 2014, University of Johannesburg

URL: http://hdl.handle.net/10210/11773

►

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Visser, Hendrik Marthinus. “The neural modelling of a direct reduction process.” 2014. Thesis, University of Johannesburg. Accessed February 26, 2021. http://hdl.handle.net/10210/11773.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Visser, Hendrik Marthinus. “The neural modelling of a direct reduction process.” 2014. Web. 26 Feb 2021.

Vancouver:

Visser HM. The neural modelling of a direct reduction process. [Internet] [Thesis]. University of Johannesburg; 2014. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10210/11773.

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

Not specified: Masters Thesis or Doctoral Dissertation

29.
Munteanu, Alexander.
On large-scale probabilistic and statistical *data* analysis.

Degree: 2018, Technische Universität Dortmund

URL: http://dx.doi.org/10.17877/DE290R-19112

► In this manuscript we develop and apply modern algorithmic *data* *reduction* techniques to tackle scalability issues and enable statistical *data* analysis of massive *data* sets.…
(more)

Subjects/Keywords: Data reduction; Regression; Random projections; Coresets; 004; Datenkompression; Regressionsanalyse; Dimensionsreduktion

Record Details Similar Records

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

APA (6^{th} Edition):

Munteanu, A. (2018). On large-scale probabilistic and statistical data analysis. (Doctoral Dissertation). Technische Universität Dortmund. Retrieved from http://dx.doi.org/10.17877/DE290R-19112

Chicago Manual of Style (16^{th} Edition):

Munteanu, Alexander. “On large-scale probabilistic and statistical data analysis.” 2018. Doctoral Dissertation, Technische Universität Dortmund. Accessed February 26, 2021. http://dx.doi.org/10.17877/DE290R-19112.

MLA Handbook (7^{th} Edition):

Munteanu, Alexander. “On large-scale probabilistic and statistical data analysis.” 2018. Web. 26 Feb 2021.

Vancouver:

Munteanu A. On large-scale probabilistic and statistical data analysis. [Internet] [Doctoral dissertation]. Technische Universität Dortmund; 2018. [cited 2021 Feb 26]. Available from: http://dx.doi.org/10.17877/DE290R-19112.

Council of Science Editors:

Munteanu A. On large-scale probabilistic and statistical data analysis. [Doctoral Dissertation]. Technische Universität Dortmund; 2018. Available from: http://dx.doi.org/10.17877/DE290R-19112

University of Ontario Institute of Technology

30. Fernandez Espinosa, Arturo. Cluster techniques and prediction models for a digital media learning environment.

Degree: 2012, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/241

► The present work applies well-known *data* mining techniques in a digital learning media environment in order to identify groups of students based on their pro…
(more)

Subjects/Keywords: Data mining; Neural networks; Custer techniques; Learning; Dimensionality reduction

Record Details Similar Records

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

APA (6^{th} Edition):

Fernandez Espinosa, A. (2012). Cluster techniques and prediction models for a digital media learning environment. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/241

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Fernandez Espinosa, Arturo. “Cluster techniques and prediction models for a digital media learning environment.” 2012. Thesis, University of Ontario Institute of Technology. Accessed February 26, 2021. http://hdl.handle.net/10155/241.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Fernandez Espinosa, Arturo. “Cluster techniques and prediction models for a digital media learning environment.” 2012. Web. 26 Feb 2021.

Vancouver:

Fernandez Espinosa A. Cluster techniques and prediction models for a digital media learning environment. [Internet] [Thesis]. University of Ontario Institute of Technology; 2012. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10155/241.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fernandez Espinosa A. Cluster techniques and prediction models for a digital media learning environment. [Thesis]. University of Ontario Institute of Technology; 2012. Available from: http://hdl.handle.net/10155/241

Not specified: Masters Thesis or Doctoral Dissertation