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You searched for subject:(Dimensionality reduction). Showing records 1 – 30 of 282 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 February 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 Feb 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 Feb 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 February 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 Feb 2020.

Vancouver:

Ibrahim Abdelhalim AA. Analysis of Twitter Hashtags' Geographic Propagation. [Internet] [Thesis]. Texas A&M University; 2016. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Onclinx V. Dimensionality reduction for visualization : representing on manifolds and preserving ranks. [Internet] [Thesis]. Université Catholique de Louvain; 2015. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Khajehpour Tadavani P. Nonlinear Dimensionality Reduction by Manifold Unfolding. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2020 Feb 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 February 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 Feb 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 Feb 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 February 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 Feb 2020.

Vancouver:

Tsagkatakis G. Dimensionality reduction and sparse representations in computer vision. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2020 Feb 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 February 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 Feb 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 Feb 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 February 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 Feb 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 Feb 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 February 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 Feb 2020.

Vancouver:

Yang H. DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Wilkinson D. Subjective Mapping. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Feb 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 February 28, 2020. http://hdl.handle.net/10251/10939.

MLA Handbook (7th Edition):

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

Vancouver:

Villegas Santamaría M. Contributions to High-Dimensional Pattern Recognition . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2011. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Helsing J. A Case Study on Test Optimisation and Visualisation of Diversity Information . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Holiday A. Manifold learning for coarse-graining networks and for parameter reduction . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2020 Feb 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 February 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 Feb 2020.

Vancouver:

Li Q. Online sufficient dimensionality reduction for sequential high-dimensional time-series. [Internet] [Masters thesis]. Georgia Tech; 2015. [cited 2020 Feb 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 February 28, 2020. https://etda.libraries.psu.edu/catalog/7941.

MLA Handbook (7th Edition):

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

Vancouver:

Yang X. Computational Methods for Manifold learning. [Internet] [Doctoral dissertation]. Penn State University; 2007. [cited 2020 Feb 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


University of Ontario Institute of Technology

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

Degree: 2012, University of Ontario Institute of Technology

 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

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

APA (6th 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

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):

Fernandez Espinosa, Arturo. “Cluster techniques and prediction models for a digital media learning environment.” 2012. Thesis, University of Ontario Institute of Technology. Accessed February 28, 2020. http://hdl.handle.net/10155/241.

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

MLA Handbook (7th Edition):

Fernandez Espinosa, Arturo. “Cluster techniques and prediction models for a digital media learning environment.” 2012. Web. 28 Feb 2020.

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 2020 Feb 28]. Available from: http://hdl.handle.net/10155/241.

Note: this citation may be lacking information needed for this citation format:
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

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


Carnegie Mellon University

17. 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 February 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 Feb 2020.

Vancouver:

Bishop W. Combining Neural Population Recordings: Theory and Application. [Internet] [Thesis]. Carnegie Mellon University; 2015. [cited 2020 Feb 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

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

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 February 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 Feb 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 Feb 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 Minnesota

19. Li, Xingguo. Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications.

Degree: PhD, Electrical Engineering, 2018, University of Minnesota

 In modern ``Big Data'' applications, structured learning is the most widely employed methodology. Within this paradigm, the fundamental challenge lies in developing practical, effective algorithmic… (more)

Subjects/Keywords: big data application; dimensionality reduction; nonconvex optimization; structured learning

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

APA (6th Edition):

Li, X. (2018). Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/200308

Chicago Manual of Style (16th Edition):

Li, Xingguo. “Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications.” 2018. Doctoral Dissertation, University of Minnesota. Accessed February 28, 2020. http://hdl.handle.net/11299/200308.

MLA Handbook (7th Edition):

Li, Xingguo. “Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications.” 2018. Web. 28 Feb 2020.

Vancouver:

Li X. Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications. [Internet] [Doctoral dissertation]. University of Minnesota; 2018. [cited 2020 Feb 28]. Available from: http://hdl.handle.net/11299/200308.

Council of Science Editors:

Li X. Structured Learning with Parsimony in Measurements and Computations: Theory, Algorithms, and Applications. [Doctoral Dissertation]. University of Minnesota; 2018. Available from: http://hdl.handle.net/11299/200308


University of Minnesota

20. Bermperidis, Dimitrios. Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data.

Degree: M.S.E.E., Electrical Engineering, 2015, University of Minnesota

 In an age of exponentially increasing data availability, performing inference tasks by utilizing the available information in its entirety is not always an affordable option.… (more)

Subjects/Keywords: censoring; computational complexity; dimensionality reduction; dynamical processes; linear regression; tracking

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

APA (6th Edition):

Bermperidis, D. (2015). Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/175484

Chicago Manual of Style (16th Edition):

Bermperidis, Dimitrios. “Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data.” 2015. Masters Thesis, University of Minnesota. Accessed February 28, 2020. http://hdl.handle.net/11299/175484.

MLA Handbook (7th Edition):

Bermperidis, Dimitrios. “Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data.” 2015. Web. 28 Feb 2020.

Vancouver:

Bermperidis D. Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data. [Internet] [Masters thesis]. University of Minnesota; 2015. [cited 2020 Feb 28]. Available from: http://hdl.handle.net/11299/175484.

Council of Science Editors:

Bermperidis D. Online Censoring for Large-Scale Regressions and Dynamical Processes with Application to Big Data. [Masters Thesis]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/175484


University of Minnesota

21. Kumar, Arjun. A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data.

Degree: MS, Computer Science, 2015, University of Minnesota

Dimensionality reduction is a significant problem across a wide variety of domains such as pattern recognition, data compression, image segmentation and clustering. Different methods exploit… (more)

Subjects/Keywords: Data mining; climate; dimensionality reduction; Non linear; PCA

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

APA (6th Edition):

Kumar, A. (2015). A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/175724

Chicago Manual of Style (16th Edition):

Kumar, Arjun. “A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data.” 2015. Masters Thesis, University of Minnesota. Accessed February 28, 2020. http://hdl.handle.net/11299/175724.

MLA Handbook (7th Edition):

Kumar, Arjun. “A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data.” 2015. Web. 28 Feb 2020.

Vancouver:

Kumar A. A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data. [Internet] [Masters thesis]. University of Minnesota; 2015. [cited 2020 Feb 28]. Available from: http://hdl.handle.net/11299/175724.

Council of Science Editors:

Kumar A. A Study of Dimensionality Reduction Techniques and its Analysis on Climate Data. [Masters Thesis]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/175724


University of Illinois – Urbana-Champaign

22. Bharadwaj, Sujeeth. Multiview feature learning for speech recognition.

Degree: MS, 1200, 2012, University of Illinois – Urbana-Champaign

 In this thesis, we study the problem of learning a linear transformation of acoustic feature vectors for speech recognition, in a framework where apart from… (more)

Subjects/Keywords: Multiview learning; canonical correlation analysis; articulatory measurements; dimensionality reduction; acoustic features

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APA (6th Edition):

Bharadwaj, S. (2012). Multiview feature learning for speech recognition. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/29785

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):

Bharadwaj, Sujeeth. “Multiview feature learning for speech recognition.” 2012. Thesis, University of Illinois – Urbana-Champaign. Accessed February 28, 2020. http://hdl.handle.net/2142/29785.

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

MLA Handbook (7th Edition):

Bharadwaj, Sujeeth. “Multiview feature learning for speech recognition.” 2012. Web. 28 Feb 2020.

Vancouver:

Bharadwaj S. Multiview feature learning for speech recognition. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2012. [cited 2020 Feb 28]. Available from: http://hdl.handle.net/2142/29785.

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

Council of Science Editors:

Bharadwaj S. Multiview feature learning for speech recognition. [Thesis]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/29785

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


University of Illinois – Urbana-Champaign

23. Ramachandran, Chandrasekar. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.

Degree: MS, 0112, 2010, University of Illinois – Urbana-Champaign

 In this work, we describe a comprehensive framework for knowledge discovery from medical records called SDM-Miner. The records are created before, during and after pancreatic… (more)

Subjects/Keywords: islet cell transplants; medical data mining; dimensionality reduction; association rule mining

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APA (6th Edition):

Ramachandran, C. (2010). A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/14710

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):

Ramachandran, Chandrasekar. “A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed February 28, 2020. http://hdl.handle.net/2142/14710.

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

MLA Handbook (7th Edition):

Ramachandran, Chandrasekar. “A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.” 2010. Web. 28 Feb 2020.

Vancouver:

Ramachandran C. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2020 Feb 28]. Available from: http://hdl.handle.net/2142/14710.

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

Council of Science Editors:

Ramachandran C. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/14710

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


University of Waikato

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

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 February 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 Feb 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 Feb 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

25. 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 February 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 Feb 2020.

Vancouver:

Qiao M. Visual Analytics Through Gaussian Mixture Models with Subspace Constrained Component Means. [Internet] [Thesis]. Penn State University; 2017. [cited 2020 Feb 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

26. 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 February 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 Feb 2020.

Vancouver:

Tian TS. Dimensionality reduction for classification with high-dimensional data. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2020 Feb 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

27. 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 February 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 Feb 2020.

Vancouver:

Tai C. On the sampling design of high-dimensional signal in distributed detection through dimensionality reduction. [Internet] [Thesis]. NSYSU; 2008. [cited 2020 Feb 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

28. 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 February 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 Feb 2020.

Vancouver:

Silva SM. Redução de dimensionalidade aplicada à diarização de locutor. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2013. [cited 2020 Feb 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

29. 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 (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 February 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 Feb 2020.

Vancouver:

Sharma VM. AN EVALUATION OF DIMENSIONALITY REDUCTION ON CELL FORMATION EFFICACY. [Internet] [Masters thesis]. Ohio University; 2007. [cited 2020 Feb 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

30. 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 February 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 Feb 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 Feb 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

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