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You searched for subject:(dimensionality reduction). Showing records 1 – 30 of 288 total matches.

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Université Catholique de Louvain

1. Jansen, Arthur. Analysis of the Financial Times ranking "master in management" with machine learning.

Degree: 2017, Université Catholique de Louvain

University rankings play nowadays a major role in the decision of many students with regards to their future schools. Nonetheless, these rankings often remain quite… (more)

Subjects/Keywords: Machine learning; Ranking; Dimensionality reduction

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APA (6th Edition):

Jansen, A. (2017). Analysis of the Financial Times ranking "master in management" with machine learning. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:10638

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):

Jansen, Arthur. “Analysis of the Financial Times ranking "master in management" with machine learning.” 2017. Thesis, Université Catholique de Louvain. Accessed March 28, 2020. http://hdl.handle.net/2078.1/thesis:10638.

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

MLA Handbook (7th Edition):

Jansen, Arthur. “Analysis of the Financial Times ranking "master in management" with machine learning.” 2017. Web. 28 Mar 2020.

Vancouver:

Jansen A. Analysis of the Financial Times ranking "master in management" with machine learning. [Internet] [Thesis]. Université Catholique de Louvain; 2017. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/2078.1/thesis:10638.

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

Council of Science Editors:

Jansen A. Analysis of the Financial Times ranking "master in management" with machine learning. [Thesis]. Université Catholique de Louvain; 2017. Available from: http://hdl.handle.net/2078.1/thesis:10638

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


Texas A&M University

2. Ibrahim Abdelhalim, Ashraf A. Analysis of Twitter Hashtags' Geographic Propagation.

Degree: 2016, Texas A&M University

 The goal of this work is to study the geographic propagation patterns of Twitters' hashtags. In order to analyze the hashtags' diffusion patterns, we look… (more)

Subjects/Keywords: Information Diffusion; dimensionality reduction

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APA (6th Edition):

Ibrahim Abdelhalim, A. A. (2016). Analysis of Twitter Hashtags' Geographic Propagation. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156300

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):

Ibrahim Abdelhalim, Ashraf A. “Analysis of Twitter Hashtags' Geographic Propagation.” 2016. Thesis, Texas A&M University. Accessed March 28, 2020. http://hdl.handle.net/1969.1/156300.

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

MLA Handbook (7th Edition):

Ibrahim Abdelhalim, Ashraf A. “Analysis of Twitter Hashtags' Geographic Propagation.” 2016. Web. 28 Mar 2020.

Vancouver:

Ibrahim Abdelhalim AA. Analysis of Twitter Hashtags' Geographic Propagation. [Internet] [Thesis]. Texas A&M University; 2016. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1969.1/156300.

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

Council of Science Editors:

Ibrahim Abdelhalim AA. Analysis of Twitter Hashtags' Geographic Propagation. [Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/156300

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


Université Catholique de Louvain

3. Onclinx, Victor. Dimensionality reduction for visualization : representing on manifolds and preserving ranks.

Degree: 2015, Université Catholique de Louvain

Because of the increasing facility to collect and to store large amounts of features, industrial and research fields have more and more to deal with… (more)

Subjects/Keywords: Dimensionality reduction; Visualization; Ranks; Manifolds

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APA (6th Edition):

Onclinx, V. (2015). Dimensionality reduction for visualization : representing on manifolds and preserving ranks. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/160847

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):

Onclinx, Victor. “Dimensionality reduction for visualization : representing on manifolds and preserving ranks.” 2015. Thesis, Université Catholique de Louvain. Accessed March 28, 2020. http://hdl.handle.net/2078.1/160847.

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

MLA Handbook (7th Edition):

Onclinx, Victor. “Dimensionality reduction for visualization : representing on manifolds and preserving ranks.” 2015. Web. 28 Mar 2020.

Vancouver:

Onclinx V. Dimensionality reduction for visualization : representing on manifolds and preserving ranks. [Internet] [Thesis]. Université Catholique de Louvain; 2015. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/2078.1/160847.

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

Council of Science Editors:

Onclinx V. Dimensionality reduction for visualization : representing on manifolds and preserving ranks. [Thesis]. Université Catholique de Louvain; 2015. Available from: http://hdl.handle.net/2078.1/160847

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


University of Waterloo

4. Khajehpour Tadavani, Pooyan. Nonlinear Dimensionality Reduction by Manifold Unfolding.

Degree: 2013, University of Waterloo

 Every second, an enormous volume of data is being gathered from various sources and stored in huge data banks. Most of the time, monitoring a… (more)

Subjects/Keywords: Dimensionality Reduction; Manifold Unfolding

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APA (6th Edition):

Khajehpour Tadavani, P. (2013). Nonlinear Dimensionality Reduction by Manifold Unfolding. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/7947

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):

Khajehpour Tadavani, Pooyan. “Nonlinear Dimensionality Reduction by Manifold Unfolding.” 2013. Thesis, University of Waterloo. Accessed March 28, 2020. http://hdl.handle.net/10012/7947.

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

MLA Handbook (7th Edition):

Khajehpour Tadavani, Pooyan. “Nonlinear Dimensionality Reduction by Manifold Unfolding.” 2013. Web. 28 Mar 2020.

Vancouver:

Khajehpour Tadavani P. Nonlinear Dimensionality Reduction by Manifold Unfolding. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10012/7947.

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

Council of Science Editors:

Khajehpour Tadavani P. Nonlinear Dimensionality Reduction by Manifold Unfolding. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/7947

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 (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 28, 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. 28 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 28]. 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


Rochester Institute of Technology

6. Tsagkatakis, Grigorios. Dimensionality reduction and sparse representations in computer vision.

Degree: Chester F. Carlson Center for Imaging Science (COS), 2011, Rochester Institute of Technology

 The proliferation of camera equipped devices, such as netbooks, smartphones and game stations, has led to a significant increase in the production of visual content.… (more)

Subjects/Keywords: Computer vision; Dimensionality reduction; Smartphones; Sparse representations

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APA (6th Edition):

Tsagkatakis, G. (2011). Dimensionality reduction and sparse representations in computer vision. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/2964

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):

Tsagkatakis, Grigorios. “Dimensionality reduction and sparse representations in computer vision.” 2011. Thesis, Rochester Institute of Technology. Accessed March 28, 2020. https://scholarworks.rit.edu/theses/2964.

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

MLA Handbook (7th Edition):

Tsagkatakis, Grigorios. “Dimensionality reduction and sparse representations in computer vision.” 2011. Web. 28 Mar 2020.

Vancouver:

Tsagkatakis G. Dimensionality reduction and sparse representations in computer vision. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2020 Mar 28]. Available from: https://scholarworks.rit.edu/theses/2964.

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

Council of Science Editors:

Tsagkatakis G. Dimensionality reduction and sparse representations in computer vision. [Thesis]. Rochester Institute of Technology; 2011. Available from: https://scholarworks.rit.edu/theses/2964

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


University of Southern California

7. Shu, (Allen) Yu-Hsiang. Pathway-based analysis of multivariate traits using classical dimensionality reduction methods.

Degree: PhD, Statistical Genetics and Genetic Epidemiology, 2015, University of Southern California

Dimensionality reduction methods (DRMs) can capture important information of the data with fewer components, and testing those components can improve power in association testing. My… (more)

Subjects/Keywords: pathway-based analysis; dimensionality reduction; permutation test

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APA (6th Edition):

Shu, (. Y. (2015). Pathway-based analysis of multivariate traits using classical dimensionality reduction methods. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/528610/rec/4949

Chicago Manual of Style (16th Edition):

Shu, (Allen) Yu-Hsiang. “Pathway-based analysis of multivariate traits using classical dimensionality reduction methods.” 2015. Doctoral Dissertation, University of Southern California. Accessed March 28, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/528610/rec/4949.

MLA Handbook (7th Edition):

Shu, (Allen) Yu-Hsiang. “Pathway-based analysis of multivariate traits using classical dimensionality reduction methods.” 2015. Web. 28 Mar 2020.

Vancouver:

Shu (Y. Pathway-based analysis of multivariate traits using classical dimensionality reduction methods. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Mar 28]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/528610/rec/4949.

Council of Science Editors:

Shu (Y. Pathway-based analysis of multivariate traits using classical dimensionality reduction methods. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/528610/rec/4949


Rochester Institute of Technology

8. Zhang, Xuewen. Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery.

Degree: PhD, Chester F. Carlson Center for Imaging Science (COS), 2019, Rochester Institute of Technology

  Classification, target detection, and compression are all important tasks in analyzing hyperspectral imagery (HSI). Because of the high dimensionality of HSI, it is often… (more)

Subjects/Keywords: Autoencoder; Hyperspectral image; Nonlinear dimensionality reduction; Superpixel

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

APA (6th Edition):

Zhang, X. (2019). Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery. (Doctoral Dissertation). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9984

Chicago Manual of Style (16th Edition):

Zhang, Xuewen. “Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery.” 2019. Doctoral Dissertation, Rochester Institute of Technology. Accessed March 28, 2020. https://scholarworks.rit.edu/theses/9984.

MLA Handbook (7th Edition):

Zhang, Xuewen. “Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery.” 2019. Web. 28 Mar 2020.

Vancouver:

Zhang X. Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery. [Internet] [Doctoral dissertation]. Rochester Institute of Technology; 2019. [cited 2020 Mar 28]. Available from: https://scholarworks.rit.edu/theses/9984.

Council of Science Editors:

Zhang X. Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery. [Doctoral Dissertation]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/9984


Mississippi State University

9. Yang, He. DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY.

Degree: PhD, Electrical and Computer Engineering, 2011, Mississippi State University

 In this dissertation, dimensionality reduction for hyperspectral remote sensing imagery is investigated to alleviate practical application difficulties caused by high data dimension. Band selection and… (more)

Subjects/Keywords: hyperspectral; dimensionality reduction; band selection; gpu

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APA (6th Edition):

Yang, H. (2011). DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-03292011-114424/ ;

Chicago Manual of Style (16th Edition):

Yang, He. “DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY.” 2011. Doctoral Dissertation, Mississippi State University. Accessed March 28, 2020. http://sun.library.msstate.edu/ETD-db/theses/available/etd-03292011-114424/ ;.

MLA Handbook (7th Edition):

Yang, He. “DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY.” 2011. Web. 28 Mar 2020.

Vancouver:

Yang H. DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2020 Mar 28]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03292011-114424/ ;.

Council of Science Editors:

Yang H. DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY. [Doctoral Dissertation]. Mississippi State University; 2011. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03292011-114424/ ;


University of Waterloo

10. Wilkinson, Dana. Subjective Mapping.

Degree: 2007, University of Waterloo

 There are a variety of domains where it is desirable to learn a representation of an environment defined by a stream of sensori-motor experience. This… (more)

Subjects/Keywords: mapping; dimensionality reduction

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APA (6th Edition):

Wilkinson, D. (2007). Subjective Mapping. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3423

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):

Wilkinson, Dana. “Subjective Mapping.” 2007. Thesis, University of Waterloo. Accessed March 28, 2020. http://hdl.handle.net/10012/3423.

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

MLA Handbook (7th Edition):

Wilkinson, Dana. “Subjective Mapping.” 2007. Web. 28 Mar 2020.

Vancouver:

Wilkinson D. Subjective Mapping. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10012/3423.

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

Council of Science Editors:

Wilkinson D. Subjective Mapping. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/3423

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


Universitat Politècnica de València

11. Villegas Santamaría, Mauricio. Contributions to High-Dimensional Pattern Recognition .

Degree: 2011, Universitat Politècnica de València

 This thesis gathers some contributions to statistical pattern recognition particularly targeted at problems in which the feature vectors are high-dimensional. Three pattern recognition scenarios are… (more)

Subjects/Keywords: Pattern recognition; Dimensionality reduction; Classification; Regression; Ranking

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APA (6th Edition):

Villegas Santamaría, M. (2011). Contributions to High-Dimensional Pattern Recognition . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/10939

Chicago Manual of Style (16th Edition):

Villegas Santamaría, Mauricio. “Contributions to High-Dimensional Pattern Recognition .” 2011. Doctoral Dissertation, Universitat Politècnica de València. Accessed March 28, 2020. http://hdl.handle.net/10251/10939.

MLA Handbook (7th Edition):

Villegas Santamaría, Mauricio. “Contributions to High-Dimensional Pattern Recognition .” 2011. Web. 28 Mar 2020.

Vancouver:

Villegas Santamaría M. Contributions to High-Dimensional Pattern Recognition . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2011. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10251/10939.

Council of Science Editors:

Villegas Santamaría M. Contributions to High-Dimensional Pattern Recognition . [Doctoral Dissertation]. Universitat Politècnica de València; 2011. Available from: http://hdl.handle.net/10251/10939

12. Helsing, Jonathan. A Case Study on Test Optimisation and Visualisation of Diversity Information .

Degree: Chalmers tekniska högskola / Institutionen för data och informationsvetenskap, 2019, Chalmers University of Technology

 Continuous Integration (CI) pipelines are vital in the implementation of CI and in the feedback cycles that surround automated testing in CI environments. A feedback… (more)

Subjects/Keywords: prioritisation; diversity; dimensionality reduction; continuous integration; similarity

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APA (6th Edition):

Helsing, J. (2019). A Case Study on Test Optimisation and Visualisation of Diversity Information . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300143

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):

Helsing, Jonathan. “A Case Study on Test Optimisation and Visualisation of Diversity Information .” 2019. Thesis, Chalmers University of Technology. Accessed March 28, 2020. http://hdl.handle.net/20.500.12380/300143.

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

MLA Handbook (7th Edition):

Helsing, Jonathan. “A Case Study on Test Optimisation and Visualisation of Diversity Information .” 2019. Web. 28 Mar 2020.

Vancouver:

Helsing J. A Case Study on Test Optimisation and Visualisation of Diversity Information . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/20.500.12380/300143.

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

Council of Science Editors:

Helsing J. A Case Study on Test Optimisation and Visualisation of Diversity Information . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/300143

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

13. Holiday, Alexander. Manifold learning for coarse-graining networks and for parameter reduction .

Degree: PhD, 2017, Princeton University

 Recent decades have seen a tremendous rise in the affordability and performance of various computational technologies, enabling researchers to propose and probe ever more complicated… (more)

Subjects/Keywords: diffusion maps; dimensionality reduction; manifold learning; networks; parameter reduction

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APA (6th Edition):

Holiday, A. (2017). Manifold learning for coarse-graining networks and for parameter reduction . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01j098zd77v

Chicago Manual of Style (16th Edition):

Holiday, Alexander. “Manifold learning for coarse-graining networks and for parameter reduction .” 2017. Doctoral Dissertation, Princeton University. Accessed March 28, 2020. http://arks.princeton.edu/ark:/88435/dsp01j098zd77v.

MLA Handbook (7th Edition):

Holiday, Alexander. “Manifold learning for coarse-graining networks and for parameter reduction .” 2017. Web. 28 Mar 2020.

Vancouver:

Holiday A. Manifold learning for coarse-graining networks and for parameter reduction . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2020 Mar 28]. Available from: http://arks.princeton.edu/ark:/88435/dsp01j098zd77v.

Council of Science Editors:

Holiday A. Manifold learning for coarse-graining networks and for parameter reduction . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp01j098zd77v


Georgia Tech

14. Li, Qingbin. Online sufficient dimensionality reduction for sequential high-dimensional time-series.

Degree: MS, Industrial and Systems Engineering, 2015, Georgia Tech

In this thesis, we present Online Sufficient Dimensionality Reduction (OSDR) algorithm for real-time high-dimensional sequential data analysis. Advisors/Committee Members: Xie, Yao (advisor), Song, Le (committee member), Zhou, Enlu (committee member).

Subjects/Keywords: Online learning; Dimension reduction; Sufficient dimensionality reduction; Stochastic gradient descent

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APA (6th Edition):

Li, Q. (2015). Online sufficient dimensionality reduction for sequential high-dimensional time-series. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60385

Chicago Manual of Style (16th Edition):

Li, Qingbin. “Online sufficient dimensionality reduction for sequential high-dimensional time-series.” 2015. Masters Thesis, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/60385.

MLA Handbook (7th Edition):

Li, Qingbin. “Online sufficient dimensionality reduction for sequential high-dimensional time-series.” 2015. Web. 28 Mar 2020.

Vancouver:

Li Q. Online sufficient dimensionality reduction for sequential high-dimensional time-series. [Internet] [Masters thesis]. Georgia Tech; 2015. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/60385.

Council of Science Editors:

Li Q. Online sufficient dimensionality reduction for sequential high-dimensional time-series. [Masters Thesis]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/60385


Penn State University

15. Yang, Xin. Computational Methods for Manifold learning.

Degree: PhD, Computer Science and Engineering, 2007, Penn State University

 In many real world applications, data samples lying in a high dimensional ambient space can be modeled by very low dimensional nonlinear manifolds. Manifold learning,… (more)

Subjects/Keywords: dimensionality estimator; dimensionality reduction; manifold learning

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APA (6th Edition):

Yang, X. (2007). Computational Methods for Manifold learning. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/7941

Chicago Manual of Style (16th Edition):

Yang, Xin. “Computational Methods for Manifold learning.” 2007. Doctoral Dissertation, Penn State University. Accessed March 28, 2020. https://etda.libraries.psu.edu/catalog/7941.

MLA Handbook (7th Edition):

Yang, Xin. “Computational Methods for Manifold learning.” 2007. Web. 28 Mar 2020.

Vancouver:

Yang X. Computational Methods for Manifold learning. [Internet] [Doctoral dissertation]. Penn State University; 2007. [cited 2020 Mar 28]. Available from: https://etda.libraries.psu.edu/catalog/7941.

Council of Science Editors:

Yang X. Computational Methods for Manifold learning. [Doctoral Dissertation]. Penn State University; 2007. Available from: https://etda.libraries.psu.edu/catalog/7941


Carnegie Mellon University

16. Bishop, William. Combining Neural Population Recordings: Theory and Application.

Degree: 2015, Carnegie Mellon University

 Modern electrophysiological and optical recording techniques allow for the simultaneous monitoring of large populations of neurons. However, current technologies are still limited in the total… (more)

Subjects/Keywords: neural recordings; stitching; electrophysiology; optical methods; dimensionality reduction; matrix completion

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

APA (6th Edition):

Bishop, W. (2015). Combining Neural Population Recordings: Theory and Application. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1223

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):

Bishop, William. “Combining Neural Population Recordings: Theory and Application.” 2015. Thesis, Carnegie Mellon University. Accessed March 28, 2020. http://repository.cmu.edu/dissertations/1223.

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

MLA Handbook (7th Edition):

Bishop, William. “Combining Neural Population Recordings: Theory and Application.” 2015. Web. 28 Mar 2020.

Vancouver:

Bishop W. Combining Neural Population Recordings: Theory and Application. [Internet] [Thesis]. Carnegie Mellon University; 2015. [cited 2020 Mar 28]. Available from: http://repository.cmu.edu/dissertations/1223.

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

Council of Science Editors:

Bishop W. Combining Neural Population Recordings: Theory and Application. [Thesis]. Carnegie Mellon University; 2015. Available from: http://repository.cmu.edu/dissertations/1223

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

17. Jerald Beno,T R. Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;.

Degree: Applied Electronics and computer science, 2012, Manonmaniam Sundaranar University

None

References p. 143-153, Appendix p. 154-178

Advisors/Committee Members: Karnan,M.

Subjects/Keywords: Approach; Cancer; Dimensionality; Reduction; Technique

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APA (6th Edition):

R, J. B. (2012). Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;. (Thesis). Manonmaniam Sundaranar University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/29332

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):

R, Jerald Beno,T. “Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;.” 2012. Thesis, Manonmaniam Sundaranar University. Accessed March 28, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/29332.

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

MLA Handbook (7th Edition):

R, Jerald Beno,T. “Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;.” 2012. Web. 28 Mar 2020.

Vancouver:

R JB. Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;. [Internet] [Thesis]. Manonmaniam Sundaranar University; 2012. [cited 2020 Mar 28]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/29332.

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

Council of Science Editors:

R JB. Dimensionality reduction a new approach to reduct Cancer dataset using relative reduct technique;. [Thesis]. Manonmaniam Sundaranar University; 2012. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/29332

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


University of Waikato

18. Pham, Thi Hong Lien. Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms .

Degree: 2018, University of Waikato

 Remote sensing technology is an efficient tool for various practical applications of environmental resources management. Advances in this technology include the diverse range of high… (more)

Subjects/Keywords: object-based classification; dimensionality reduction; biomass change; mangrove; LiDAR; machine learning

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APA (6th Edition):

Pham, T. H. L. (2018). Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms . (Doctoral Dissertation). University of Waikato. Retrieved from http://hdl.handle.net/10289/11758

Chicago Manual of Style (16th Edition):

Pham, Thi Hong Lien. “Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms .” 2018. Doctoral Dissertation, University of Waikato. Accessed March 28, 2020. http://hdl.handle.net/10289/11758.

MLA Handbook (7th Edition):

Pham, Thi Hong Lien. “Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms .” 2018. Web. 28 Mar 2020.

Vancouver:

Pham THL. Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms . [Internet] [Doctoral dissertation]. University of Waikato; 2018. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10289/11758.

Council of Science Editors:

Pham THL. Mapping vegetation with remote sensing and GIS data using object-based analysis and machine learning algorithms . [Doctoral Dissertation]. University of Waikato; 2018. Available from: http://hdl.handle.net/10289/11758


Penn State University

19. Qiao, Mu. Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means.

Degree: 2017, Penn State University

 We develop a new method for high dimensional data visualization via the Gaussian mixture model (GMM) with the component means constrained in a pre-selected subspace.… (more)

Subjects/Keywords: visualization; high dimensionality; dimension reduction; subspace; Gaussian mixture model

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APA (6th Edition):

Qiao, M. (2017). Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means. (Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/14721muq103

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):

Qiao, Mu. “Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means.” 2017. Thesis, Penn State University. Accessed March 28, 2020. https://etda.libraries.psu.edu/catalog/14721muq103.

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

MLA Handbook (7th Edition):

Qiao, Mu. “Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means.” 2017. Web. 28 Mar 2020.

Vancouver:

Qiao M. Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means. [Internet] [Thesis]. Penn State University; 2017. [cited 2020 Mar 28]. Available from: https://etda.libraries.psu.edu/catalog/14721muq103.

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

Council of Science Editors:

Qiao M. Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means. [Thesis]. Penn State University; 2017. Available from: https://etda.libraries.psu.edu/catalog/14721muq103

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


University of Southern California

20. Tian, Tian Siva. Dimensionality reduction for classification with high-dimensional data.

Degree: PhD, Psychology, 2009, University of Southern California

 This thesis addresses dimensionality reduction problems in classification for both high-dimensional multivariate and functional data.; High-dimensional data refers to data with a large number of… (more)

Subjects/Keywords: dimensionality reduction; classification; variable selection; variable combination; stochastic search

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

APA (6th Edition):

Tian, T. S. (2009). Dimensionality reduction for classification with high-dimensional data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406875/rec/2006

Chicago Manual of Style (16th Edition):

Tian, Tian Siva. “Dimensionality reduction for classification with high-dimensional data.” 2009. Doctoral Dissertation, University of Southern California. Accessed March 28, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406875/rec/2006.

MLA Handbook (7th Edition):

Tian, Tian Siva. “Dimensionality reduction for classification with high-dimensional data.” 2009. Web. 28 Mar 2020.

Vancouver:

Tian TS. Dimensionality reduction for classification with high-dimensional data. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2020 Mar 28]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406875/rec/2006.

Council of Science Editors:

Tian TS. Dimensionality reduction for classification with high-dimensional data. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406875/rec/2006


NSYSU

21. Tai, Chih-hao. On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction.

Degree: Master, Communications Engineering, 2008, NSYSU

 This work considers the sampling design for detection problems.Firstly,we focus on studying the effect of signal shape on sampling design for Gaussian detection problem.We then… (more)

Subjects/Keywords: Sampling design; distributed detection; dimensionality reduction; cluster-based wireless sensor networks

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APA (6th Edition):

Tai, C. (2008). On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0813108-162917

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):

Tai, Chih-hao. “On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction.” 2008. Thesis, NSYSU. Accessed March 28, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0813108-162917.

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

MLA Handbook (7th Edition):

Tai, Chih-hao. “On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction.” 2008. Web. 28 Mar 2020.

Vancouver:

Tai C. On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction. [Internet] [Thesis]. NSYSU; 2008. [cited 2020 Mar 28]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0813108-162917.

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

Council of Science Editors:

Tai C. On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0813108-162917

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


Universidade do Rio Grande do Sul

22. Silva, Sérgio Montazzolli. Redução de dimensionalidade aplicada à diarização de locutor.

Degree: 2013, Universidade do Rio Grande do Sul

Atualmente existe uma grande quantidade de dados multimídia sendo geradas todos os dias. Estes dados são oriundos de diversas fontes, como transmissões de rádio ou… (more)

Subjects/Keywords: Processamento : Linguagem natural; Speaker diarization; Voz computacional; Discriminant analysis; Dimensionality reduction

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APA (6th Edition):

Silva, S. M. (2013). Redução de dimensionalidade aplicada à diarização de locutor. (Thesis). Universidade do Rio Grande do Sul. Retrieved from http://hdl.handle.net/10183/94745

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):

Silva, Sérgio Montazzolli. “Redução de dimensionalidade aplicada à diarização de locutor.” 2013. Thesis, Universidade do Rio Grande do Sul. Accessed March 28, 2020. http://hdl.handle.net/10183/94745.

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

MLA Handbook (7th Edition):

Silva, Sérgio Montazzolli. “Redução de dimensionalidade aplicada à diarização de locutor.” 2013. Web. 28 Mar 2020.

Vancouver:

Silva SM. Redução de dimensionalidade aplicada à diarização de locutor. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2013. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10183/94745.

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

Council of Science Editors:

Silva SM. Redução de dimensionalidade aplicada à diarização de locutor. [Thesis]. Universidade do Rio Grande do Sul; 2013. Available from: http://hdl.handle.net/10183/94745

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


Ohio University

23. Sharma, Vikas Manesh. AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY.

Degree: MS, Industrial and Manufacturing Systems Engineering (Engineering), 2007, Ohio University

 This thesis tests cell formation using a dimensionally reduced Part Machine Incidence (PMI) matrix, first proposed by Ganduri et al. Singular Value Decomposition (SVD) is… (more)

Subjects/Keywords: Engineering, Industrial; evaluation; dimensionality reduction; cell formation efficacy

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

APA (6th Edition):

Sharma, V. M. (2007). AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY. (Masters Thesis). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1174503824

Chicago Manual of Style (16th Edition):

Sharma, Vikas Manesh. “AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY.” 2007. Masters Thesis, Ohio University. Accessed March 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1174503824.

MLA Handbook (7th Edition):

Sharma, Vikas Manesh. “AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY.” 2007. Web. 28 Mar 2020.

Vancouver:

Sharma VM. AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY. [Internet] [Masters thesis]. Ohio University; 2007. [cited 2020 Mar 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1174503824.

Council of Science Editors:

Sharma VM. AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY. [Masters Thesis]. Ohio University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1174503824


University of California – Berkeley

24. Chen, Mo. High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.

Degree: Electrical Engineering & Computer Sciences, 2017, University of California – Berkeley

 Automation is becoming pervasive in everyday life, and many automated systems, such as unmanned aerial systems, autonomous cars, and many types of robots, are complex… (more)

Subjects/Keywords: Artificial intelligence; Robotics; Dimensionality reduction; Reachability analysis; Robotics; Unmanned Airspace; Verification

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APA (6th Edition):

Chen, M. (2017). High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/8m7423mq

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, Mo. “High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.” 2017. Thesis, University of California – Berkeley. Accessed March 28, 2020. http://www.escholarship.org/uc/item/8m7423mq.

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

MLA Handbook (7th Edition):

Chen, Mo. “High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.” 2017. Web. 28 Mar 2020.

Vancouver:

Chen M. High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification. [Internet] [Thesis]. University of California – Berkeley; 2017. [cited 2020 Mar 28]. Available from: http://www.escholarship.org/uc/item/8m7423mq.

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. High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification. [Thesis]. University of California – Berkeley; 2017. Available from: http://www.escholarship.org/uc/item/8m7423mq

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


University of California – Merced

25. Vladymyrov, Maksym. Large-Scale Methods for Nonlinear Manifold Learning.

Degree: Electrical Engineering and Computer Science, 2014, University of California – Merced

 High-dimensional data representation is an important problem in many different areas of science. Nowadays, it is becoming crucial to interpret the data of varying dimensionality(more)

Subjects/Keywords: Computer science; dimensionality reduction; machine learning; manifold learning; unsupervised learning

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APA (6th Edition):

Vladymyrov, M. (2014). Large-Scale Methods for Nonlinear Manifold Learning. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/9hj5v8z2

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):

Vladymyrov, Maksym. “Large-Scale Methods for Nonlinear Manifold Learning.” 2014. Thesis, University of California – Merced. Accessed March 28, 2020. http://www.escholarship.org/uc/item/9hj5v8z2.

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

MLA Handbook (7th Edition):

Vladymyrov, Maksym. “Large-Scale Methods for Nonlinear Manifold Learning.” 2014. Web. 28 Mar 2020.

Vancouver:

Vladymyrov M. Large-Scale Methods for Nonlinear Manifold Learning. [Internet] [Thesis]. University of California – Merced; 2014. [cited 2020 Mar 28]. Available from: http://www.escholarship.org/uc/item/9hj5v8z2.

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

Council of Science Editors:

Vladymyrov M. Large-Scale Methods for Nonlinear Manifold Learning. [Thesis]. University of California – Merced; 2014. Available from: http://www.escholarship.org/uc/item/9hj5v8z2

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


University of Tennessee – Knoxville

26. Moon, Sangwoo. A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis.

Degree: 2010, University of Tennessee – Knoxville

 Due to the increasing demand for high dimensional data analysis from various applications such as electrocardiogram signal analysis and gene expression analysis for cancer detection,… (more)

Subjects/Keywords: Support vector machine; independent component analysis; Hybrid dimensionality reduction; Constrained optimization

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APA (6th Edition):

Moon, S. (2010). A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/829

Chicago Manual of Style (16th Edition):

Moon, Sangwoo. “A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis.” 2010. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed March 28, 2020. https://trace.tennessee.edu/utk_graddiss/829.

MLA Handbook (7th Edition):

Moon, Sangwoo. “A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis.” 2010. Web. 28 Mar 2020.

Vancouver:

Moon S. A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2010. [cited 2020 Mar 28]. Available from: https://trace.tennessee.edu/utk_graddiss/829.

Council of Science Editors:

Moon S. A Novel Hybrid Dimensionality Reduction Method using Support Vector Machines and Independent Component Analysis. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2010. Available from: https://trace.tennessee.edu/utk_graddiss/829


Université Catholique de Louvain

27. Krier, Catherine. Non-linear models and learning for Near Infrared spectra.

Degree: 2010, Université Catholique de Louvain

Near Infrared (NIR) spectrometry is a non-destructive and relatively cheap technology which enables automated controls in various domains such as food industry or pharmaceutics. Yet,… (more)

Subjects/Keywords: Near Infrared; Machine learning; Dimensionality reduction; Clustering; Functional representation; Feature selection

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APA (6th Edition):

Krier, C. (2010). Non-linear models and learning for Near Infrared spectra. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/32234

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):

Krier, Catherine. “Non-linear models and learning for Near Infrared spectra.” 2010. Thesis, Université Catholique de Louvain. Accessed March 28, 2020. http://hdl.handle.net/2078.1/32234.

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

MLA Handbook (7th Edition):

Krier, Catherine. “Non-linear models and learning for Near Infrared spectra.” 2010. Web. 28 Mar 2020.

Vancouver:

Krier C. Non-linear models and learning for Near Infrared spectra. [Internet] [Thesis]. Université Catholique de Louvain; 2010. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/2078.1/32234.

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

Council of Science Editors:

Krier C. Non-linear models and learning for Near Infrared spectra. [Thesis]. Université Catholique de Louvain; 2010. Available from: http://hdl.handle.net/2078.1/32234

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


Virginia Tech

28. Ha, Sook Shin. Dimensionality Reduction, Feature Selection and Visualization of Biological Data.

Degree: PhD, Electrical and Computer Engineering, 2012, Virginia Tech

 Due to the high dimensionality of most biological data, it is a difficult task to directly analyze, model and visualize the data to gain biological… (more)

Subjects/Keywords: Gene Expression; Feature Selection; Dimensionality Reduction; PPI network; Pathways; Visualization; Weight

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

APA (6th Edition):

Ha, S. S. (2012). Dimensionality Reduction, Feature Selection and Visualization of Biological Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77169

Chicago Manual of Style (16th Edition):

Ha, Sook Shin. “Dimensionality Reduction, Feature Selection and Visualization of Biological Data.” 2012. Doctoral Dissertation, Virginia Tech. Accessed March 28, 2020. http://hdl.handle.net/10919/77169.

MLA Handbook (7th Edition):

Ha, Sook Shin. “Dimensionality Reduction, Feature Selection and Visualization of Biological Data.” 2012. Web. 28 Mar 2020.

Vancouver:

Ha SS. Dimensionality Reduction, Feature Selection and Visualization of Biological Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10919/77169.

Council of Science Editors:

Ha SS. Dimensionality Reduction, Feature Selection and Visualization of Biological Data. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/77169


Boston University

29. Yao, Zhaojie. Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice.

Degree: MS, Biomedical Engineering, 2016, Boston University

 Recent improvements in high performance fluorescent sensors and scientific CMOS cameras enable optical imaging of neural networks at a much larger scale. Our lab has demonstrated… (more)

Subjects/Keywords: Neurosciences; Calcium-imaging; Classical conditioning; Dimensionality reduction; Hippocampus

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

APA (6th Edition):

Yao, Z. (2016). Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice. (Masters Thesis). Boston University. Retrieved from http://hdl.handle.net/2144/19497

Chicago Manual of Style (16th Edition):

Yao, Zhaojie. “Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice.” 2016. Masters Thesis, Boston University. Accessed March 28, 2020. http://hdl.handle.net/2144/19497.

MLA Handbook (7th Edition):

Yao, Zhaojie. “Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice.” 2016. Web. 28 Mar 2020.

Vancouver:

Yao Z. Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice. [Internet] [Masters thesis]. Boston University; 2016. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/2144/19497.

Council of Science Editors:

Yao Z. Development of analysis approaches to calcium-imaging data of hippocampal neurons associated with classical conditioning in mice. [Masters Thesis]. Boston University; 2016. Available from: http://hdl.handle.net/2144/19497


University of Waterloo

30. Liang, Jiaxi. Robustness in Dimensionality Reduction.

Degree: 2016, University of Waterloo

Dimensionality reduction is widely used in many statistical applications, such as image analysis, microarray analysis, or text mining. This thesis focuses on three problems that… (more)

Subjects/Keywords: Robustness; Dimensionality reduction; Influence function; Performance measure; PCA

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APA (6th Edition):

Liang, J. (2016). Robustness in Dimensionality Reduction. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10371

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):

Liang, Jiaxi. “Robustness in Dimensionality Reduction.” 2016. Thesis, University of Waterloo. Accessed March 28, 2020. http://hdl.handle.net/10012/10371.

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

MLA Handbook (7th Edition):

Liang, Jiaxi. “Robustness in Dimensionality Reduction.” 2016. Web. 28 Mar 2020.

Vancouver:

Liang J. Robustness in Dimensionality Reduction. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10012/10371.

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

Council of Science Editors:

Liang J. Robustness in Dimensionality Reduction. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10371

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

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