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You searched for subject:(matrix completion). Showing records 1 – 30 of 64 total matches.

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New Jersey Institute of Technology

1. Wang, Yiran. Matrix completion algorithms with applications in biomedicine, e-commerce and social science.

Degree: MSin Computer Science - (M.S.), Computer Science, 2017, New Jersey Institute of Technology

  This thesis investigates matrix completion algorithms with applications in biomedicine, e-commerce and social science. In general, matrix completion algorithms work well for low rank… (more)

Subjects/Keywords: Matrix completion algorithms; Computer Sciences

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APA (6th Edition):

Wang, Y. (2017). Matrix completion algorithms with applications in biomedicine, e-commerce and social science. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/37

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):

Wang, Yiran. “Matrix completion algorithms with applications in biomedicine, e-commerce and social science.” 2017. Thesis, New Jersey Institute of Technology. Accessed December 08, 2019. https://digitalcommons.njit.edu/theses/37.

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

MLA Handbook (7th Edition):

Wang, Yiran. “Matrix completion algorithms with applications in biomedicine, e-commerce and social science.” 2017. Web. 08 Dec 2019.

Vancouver:

Wang Y. Matrix completion algorithms with applications in biomedicine, e-commerce and social science. [Internet] [Thesis]. New Jersey Institute of Technology; 2017. [cited 2019 Dec 08]. Available from: https://digitalcommons.njit.edu/theses/37.

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

Council of Science Editors:

Wang Y. Matrix completion algorithms with applications in biomedicine, e-commerce and social science. [Thesis]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/theses/37

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


Cornell University

2. Gilbert, Daniel E. Luck, Fairness and Bayesian Tensor Completion .

Degree: 2019, Cornell University

 This thesis contains papers on three diverse topics. The first topic is luck in games, and how to measure it. Game theory is the study… (more)

Subjects/Keywords: luck; matrix completion; tensor completion; Statistics; bayesian; equalized odds; fairness

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APA (6th Edition):

Gilbert, D. E. (2019). Luck, Fairness and Bayesian Tensor Completion . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/67532

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):

Gilbert, Daniel E. “Luck, Fairness and Bayesian Tensor Completion .” 2019. Thesis, Cornell University. Accessed December 08, 2019. http://hdl.handle.net/1813/67532.

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

MLA Handbook (7th Edition):

Gilbert, Daniel E. “Luck, Fairness and Bayesian Tensor Completion .” 2019. Web. 08 Dec 2019.

Vancouver:

Gilbert DE. Luck, Fairness and Bayesian Tensor Completion . [Internet] [Thesis]. Cornell University; 2019. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1813/67532.

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

Council of Science Editors:

Gilbert DE. Luck, Fairness and Bayesian Tensor Completion . [Thesis]. Cornell University; 2019. Available from: http://hdl.handle.net/1813/67532

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


Boston University

3. Ruchansky, Natali. Matrix completion with structure.

Degree: PhD, Computer Science, 2016, Boston University

 Often, data organized in matrix form contains missing entries. Further, such data has been observed to exhibit effective low-rank, and has led to interest in… (more)

Subjects/Keywords: Computer science; Data mining; Matrix completion

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APA (6th Edition):

Ruchansky, N. (2016). Matrix completion with structure. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/19743

Chicago Manual of Style (16th Edition):

Ruchansky, Natali. “Matrix completion with structure.” 2016. Doctoral Dissertation, Boston University. Accessed December 08, 2019. http://hdl.handle.net/2144/19743.

MLA Handbook (7th Edition):

Ruchansky, Natali. “Matrix completion with structure.” 2016. Web. 08 Dec 2019.

Vancouver:

Ruchansky N. Matrix completion with structure. [Internet] [Doctoral dissertation]. Boston University; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/2144/19743.

Council of Science Editors:

Ruchansky N. Matrix completion with structure. [Doctoral Dissertation]. Boston University; 2016. Available from: http://hdl.handle.net/2144/19743


Iowa State University

4. Mao, Xiaojun. Topics in matrix completion and genomic prediction.

Degree: 2018, Iowa State University

 This dissertation consists of three projects focused on low-rank modeling to deal with matrix completion problems and genomic prediction by adjusting spatial effects. One big… (more)

Subjects/Keywords: Genomic Prediction; Matrix Completion; Statistics and Probability

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APA (6th Edition):

Mao, X. (2018). Topics in matrix completion and genomic prediction. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/16632

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):

Mao, Xiaojun. “Topics in matrix completion and genomic prediction.” 2018. Thesis, Iowa State University. Accessed December 08, 2019. https://lib.dr.iastate.edu/etd/16632.

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

MLA Handbook (7th Edition):

Mao, Xiaojun. “Topics in matrix completion and genomic prediction.” 2018. Web. 08 Dec 2019.

Vancouver:

Mao X. Topics in matrix completion and genomic prediction. [Internet] [Thesis]. Iowa State University; 2018. [cited 2019 Dec 08]. Available from: https://lib.dr.iastate.edu/etd/16632.

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

Council of Science Editors:

Mao X. Topics in matrix completion and genomic prediction. [Thesis]. Iowa State University; 2018. Available from: https://lib.dr.iastate.edu/etd/16632

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


University of Minnesota

5. Sun, Ruoyu. Matrix Completion via Nonconvex Factorization: Algorithms and Theory.

Degree: PhD, Electrical/Computer Engineering, 2015, University of Minnesota

 Learning low-rank structure of the data matrix is a powerful method to deal with ``big data''. However, in many modern applications such as recommendation systems… (more)

Subjects/Keywords: alternating minimization; matrix completion; matrix factorization; nonconvex; optimization; SGD

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APA (6th Edition):

Sun, R. (2015). Matrix Completion via Nonconvex Factorization: Algorithms and Theory. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/175344

Chicago Manual of Style (16th Edition):

Sun, Ruoyu. “Matrix Completion via Nonconvex Factorization: Algorithms and Theory.” 2015. Doctoral Dissertation, University of Minnesota. Accessed December 08, 2019. http://hdl.handle.net/11299/175344.

MLA Handbook (7th Edition):

Sun, Ruoyu. “Matrix Completion via Nonconvex Factorization: Algorithms and Theory.” 2015. Web. 08 Dec 2019.

Vancouver:

Sun R. Matrix Completion via Nonconvex Factorization: Algorithms and Theory. [Internet] [Doctoral dissertation]. University of Minnesota; 2015. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11299/175344.

Council of Science Editors:

Sun R. Matrix Completion via Nonconvex Factorization: Algorithms and Theory. [Doctoral Dissertation]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/175344


University of California – Irvine

6. Pezeshkpour, Pouya. Compact Factorization of Matrices Using Generalized Round-Rank.

Degree: Electrical and Computer Engineering, 2018, University of California – Irvine

Matrix factorization is a popular machine learning technique, with applications in variety of domains, such as recommendation systems [16, 28], natural language processing [26], and… (more)

Subjects/Keywords: Electrical engineering; Computer science; Generalized Round-Rank; Linear Rank; Matrix Completion; Matrix Factorization

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APA (6th Edition):

Pezeshkpour, P. (2018). Compact Factorization of Matrices Using Generalized Round-Rank. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/9x58b95k

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):

Pezeshkpour, Pouya. “Compact Factorization of Matrices Using Generalized Round-Rank.” 2018. Thesis, University of California – Irvine. Accessed December 08, 2019. http://www.escholarship.org/uc/item/9x58b95k.

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

MLA Handbook (7th Edition):

Pezeshkpour, Pouya. “Compact Factorization of Matrices Using Generalized Round-Rank.” 2018. Web. 08 Dec 2019.

Vancouver:

Pezeshkpour P. Compact Factorization of Matrices Using Generalized Round-Rank. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/9x58b95k.

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

Council of Science Editors:

Pezeshkpour P. Compact Factorization of Matrices Using Generalized Round-Rank. [Thesis]. University of California – Irvine; 2018. Available from: http://www.escholarship.org/uc/item/9x58b95k

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


University of Minnesota

7. Sharma, Mohit. Preference modeling and Accuracy in Recommender Systems.

Degree: PhD, Computer Science, 2017, University of Minnesota

 Recommender systems are widely used to recommend the most appealing items to users. In this thesis, we focus on analyzing the accuracy of the state-of-the-art… (more)

Subjects/Keywords: Cold-Start item recommendations; Collaborative filtering; Group of items; Matrix completion; Matrix factorization; Recommender systems

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APA (6th Edition):

Sharma, M. (2017). Preference modeling and Accuracy in Recommender Systems. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/192686

Chicago Manual of Style (16th Edition):

Sharma, Mohit. “Preference modeling and Accuracy in Recommender Systems.” 2017. Doctoral Dissertation, University of Minnesota. Accessed December 08, 2019. http://hdl.handle.net/11299/192686.

MLA Handbook (7th Edition):

Sharma, Mohit. “Preference modeling and Accuracy in Recommender Systems.” 2017. Web. 08 Dec 2019.

Vancouver:

Sharma M. Preference modeling and Accuracy in Recommender Systems. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11299/192686.

Council of Science Editors:

Sharma M. Preference modeling and Accuracy in Recommender Systems. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/192686


Georgia Tech

8. Rangel Walteros, Pedro Andres. A non-asymptotic study of low-rank estimation of smooth kernels on graphs.

Degree: PhD, Mathematics, 2014, Georgia Tech

 This dissertation investigates the problem of estimating a kernel over a large graph based on a sample of noisy observations of linear measurements of the… (more)

Subjects/Keywords: Low-rank matrix completion; Kernels on graphs; High dimensional probability

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APA (6th Edition):

Rangel Walteros, P. A. (2014). A non-asymptotic study of low-rank estimation of smooth kernels on graphs. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52988

Chicago Manual of Style (16th Edition):

Rangel Walteros, Pedro Andres. “A non-asymptotic study of low-rank estimation of smooth kernels on graphs.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 08, 2019. http://hdl.handle.net/1853/52988.

MLA Handbook (7th Edition):

Rangel Walteros, Pedro Andres. “A non-asymptotic study of low-rank estimation of smooth kernels on graphs.” 2014. Web. 08 Dec 2019.

Vancouver:

Rangel Walteros PA. A non-asymptotic study of low-rank estimation of smooth kernels on graphs. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1853/52988.

Council of Science Editors:

Rangel Walteros PA. A non-asymptotic study of low-rank estimation of smooth kernels on graphs. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52988


Carnegie Mellon University

9. 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 (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 December 08, 2019. 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. 08 Dec 2019.

Vancouver:

Bishop W. Combining Neural Population Recordings: Theory and Application. [Internet] [Thesis]. Carnegie Mellon University; 2015. [cited 2019 Dec 08]. 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


University of California – Berkeley

10. Voroninski, Vladislav. PhaseLift: A Novel Methodology for Phase Retrieval.

Degree: Mathematics, 2013, University of California – Berkeley

 In many physical settings, it is difficult or impossible to measure the phase of a signal. The problem is then to recover a signal from… (more)

Subjects/Keywords: Mathematics; Applied mathematics; convex programming; matrix completion; phase retrieval; random matrices

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APA (6th Edition):

Voroninski, V. (2013). PhaseLift: A Novel Methodology for Phase Retrieval. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/5wq5c4bp

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):

Voroninski, Vladislav. “PhaseLift: A Novel Methodology for Phase Retrieval.” 2013. Thesis, University of California – Berkeley. Accessed December 08, 2019. http://www.escholarship.org/uc/item/5wq5c4bp.

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

MLA Handbook (7th Edition):

Voroninski, Vladislav. “PhaseLift: A Novel Methodology for Phase Retrieval.” 2013. Web. 08 Dec 2019.

Vancouver:

Voroninski V. PhaseLift: A Novel Methodology for Phase Retrieval. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/5wq5c4bp.

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

Council of Science Editors:

Voroninski V. PhaseLift: A Novel Methodology for Phase Retrieval. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/5wq5c4bp

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


Université Catholique de Louvain

11. Cosse, Augustin. Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution.

Degree: 2016, Université Catholique de Louvain

The thesis studies semidefinite programming relaxations for three instances of the general affine rank minimization problem. The first instance, rank one matrix completion, was known… (more)

Subjects/Keywords: Semidefinite programming relaxation; Lasserre hierarchy; Matrix completion; Blind deconvolution; Inverse scattering

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APA (6th Edition):

Cosse, A. (2016). Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/178083

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):

Cosse, Augustin. “Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution.” 2016. Thesis, Université Catholique de Louvain. Accessed December 08, 2019. http://hdl.handle.net/2078.1/178083.

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

MLA Handbook (7th Edition):

Cosse, Augustin. “Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution.” 2016. Web. 08 Dec 2019.

Vancouver:

Cosse A. Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution. [Internet] [Thesis]. Université Catholique de Louvain; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/2078.1/178083.

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

Council of Science Editors:

Cosse A. Semidefinite programming relaxations for matrix completion, inverse scattering and blind deconvolution. [Thesis]. Université Catholique de Louvain; 2016. Available from: http://hdl.handle.net/2078.1/178083

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


Iowa State University

12. Hubbard, Charles. Bilinear and parallel prediction methods.

Degree: 2017, Iowa State University

 To make accurate predictions about a system one must develop a model for that system. Bilinear models are often attractive options because they allow the… (more)

Subjects/Keywords: Bilinear; GPU; matrix completion; parallel; prediction; Computer Engineering

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APA (6th Edition):

Hubbard, C. (2017). Bilinear and parallel prediction methods. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/16147

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):

Hubbard, Charles. “Bilinear and parallel prediction methods.” 2017. Thesis, Iowa State University. Accessed December 08, 2019. https://lib.dr.iastate.edu/etd/16147.

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

MLA Handbook (7th Edition):

Hubbard, Charles. “Bilinear and parallel prediction methods.” 2017. Web. 08 Dec 2019.

Vancouver:

Hubbard C. Bilinear and parallel prediction methods. [Internet] [Thesis]. Iowa State University; 2017. [cited 2019 Dec 08]. Available from: https://lib.dr.iastate.edu/etd/16147.

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

Council of Science Editors:

Hubbard C. Bilinear and parallel prediction methods. [Thesis]. Iowa State University; 2017. Available from: https://lib.dr.iastate.edu/etd/16147

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


Colorado School of Mines

13. Yang, Dehui. Structured low-rank matrix recovery via optimization methods.

Degree: PhD, Electrical Engineering, 2018, Colorado School of Mines

 From single-molecule microscopy in biology, to collaborative filtering in recommendation systems, to quantum state tomography in physics, many scientific discoveries involve solving ill-posed inverse problems,… (more)

Subjects/Keywords: Matrix completion; Models; Super-resolution; Modal analysis; Low-rank; Optimization

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

APA (6th Edition):

Yang, D. (2018). Structured low-rank matrix recovery via optimization methods. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172154

Chicago Manual of Style (16th Edition):

Yang, Dehui. “Structured low-rank matrix recovery via optimization methods.” 2018. Doctoral Dissertation, Colorado School of Mines. Accessed December 08, 2019. http://hdl.handle.net/11124/172154.

MLA Handbook (7th Edition):

Yang, Dehui. “Structured low-rank matrix recovery via optimization methods.” 2018. Web. 08 Dec 2019.

Vancouver:

Yang D. Structured low-rank matrix recovery via optimization methods. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11124/172154.

Council of Science Editors:

Yang D. Structured low-rank matrix recovery via optimization methods. [Doctoral Dissertation]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172154


Georgia Tech

14. Cao, Yang. Poisson matrix completion and change-point detection.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

 Statistical signal processing and machine learning are very important in modern science and engineering. Many theories, methods and techniques are developed to help people extract and… (more)

Subjects/Keywords: Matrix completion; Sequential change-point detection; Robust change detection; Online learning

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APA (6th Edition):

Cao, Y. (2018). Poisson matrix completion and change-point detection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60195

Chicago Manual of Style (16th Edition):

Cao, Yang. “Poisson matrix completion and change-point detection.” 2018. Doctoral Dissertation, Georgia Tech. Accessed December 08, 2019. http://hdl.handle.net/1853/60195.

MLA Handbook (7th Edition):

Cao, Yang. “Poisson matrix completion and change-point detection.” 2018. Web. 08 Dec 2019.

Vancouver:

Cao Y. Poisson matrix completion and change-point detection. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1853/60195.

Council of Science Editors:

Cao Y. Poisson matrix completion and change-point detection. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60195


University of Waterloo

15. Rahman, Adam. Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations.

Degree: 2018, University of Waterloo

 Inherent in any multivariate data is structure, which describes the general shape and distribution of the underlying point configuration. While there are potentially many types… (more)

Subjects/Keywords: Binning; Euclidean Distance Matrix Completion; Scagnostics; Structure Retention; Statistics

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APA (6th Edition):

Rahman, A. (2018). Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13365

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):

Rahman, Adam. “Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations.” 2018. Thesis, University of Waterloo. Accessed December 08, 2019. http://hdl.handle.net/10012/13365.

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

MLA Handbook (7th Edition):

Rahman, Adam. “Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations.” 2018. Web. 08 Dec 2019.

Vancouver:

Rahman A. Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10012/13365.

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

Council of Science Editors:

Rahman A. Preserving Measured Structure During Generation and Reduction of Multivariate Point Configurations. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13365

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


University of Minnesota

16. Soni, Akshay. Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds.

Degree: PhD, Electrical Engineering, 2015, University of Minnesota

 Over the past decade, sparsity has become one of the most prevalent themes in signal processing and Big-Data applications. In general, sparsity describes the phenomenon… (more)

Subjects/Keywords: Compressive Sensing; Matrix Completion; Maximum Likelihood; Poisson Denoising; Structured Sparsity

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APA (6th Edition):

Soni, A. (2015). Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/175341

Chicago Manual of Style (16th Edition):

Soni, Akshay. “Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds.” 2015. Doctoral Dissertation, University of Minnesota. Accessed December 08, 2019. http://hdl.handle.net/11299/175341.

MLA Handbook (7th Edition):

Soni, Akshay. “Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds.” 2015. Web. 08 Dec 2019.

Vancouver:

Soni A. Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds. [Internet] [Doctoral dissertation]. University of Minnesota; 2015. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11299/175341.

Council of Science Editors:

Soni A. Structured and Sparse Signal Estimation - Fundamental Limits and Error Bounds. [Doctoral Dissertation]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/175341


University of Iowa

17. Liu, Suhui. Projected Wirtinger gradient descent for spectral compressed sensing.

Degree: PhD, Mathematics, 2017, University of Iowa

  In modern data and signal acquisition, one main challenge arises from the growing scale of data. The data acquisition devices, however, are often limited… (more)

Subjects/Keywords: Matrix Completion; Projected Wirtinger Gradient Descent; Signal Reconstruction; Mathematics

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APA (6th Edition):

Liu, S. (2017). Projected Wirtinger gradient descent for spectral compressed sensing. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/5803

Chicago Manual of Style (16th Edition):

Liu, Suhui. “Projected Wirtinger gradient descent for spectral compressed sensing.” 2017. Doctoral Dissertation, University of Iowa. Accessed December 08, 2019. https://ir.uiowa.edu/etd/5803.

MLA Handbook (7th Edition):

Liu, Suhui. “Projected Wirtinger gradient descent for spectral compressed sensing.” 2017. Web. 08 Dec 2019.

Vancouver:

Liu S. Projected Wirtinger gradient descent for spectral compressed sensing. [Internet] [Doctoral dissertation]. University of Iowa; 2017. [cited 2019 Dec 08]. Available from: https://ir.uiowa.edu/etd/5803.

Council of Science Editors:

Liu S. Projected Wirtinger gradient descent for spectral compressed sensing. [Doctoral Dissertation]. University of Iowa; 2017. Available from: https://ir.uiowa.edu/etd/5803


Virginia Tech

18. Chang, Yi Tan. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.

Degree: MS, Electrical and Computer Engineering, 2018, Virginia Tech

 This thesis consists of two projects in which various machine learning approaches and statistical analysis for the integration of biomedical data analysis were explored, developed… (more)

Subjects/Keywords: Data integration; machine learning; pathway enrichment; pathway prioritization; matrix completion; treatment recommendation.

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

APA (6th Edition):

Chang, Y. T. (2018). A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83813

Chicago Manual of Style (16th Edition):

Chang, Yi Tan. “A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.” 2018. Masters Thesis, Virginia Tech. Accessed December 08, 2019. http://hdl.handle.net/10919/83813.

MLA Handbook (7th Edition):

Chang, Yi Tan. “A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.” 2018. Web. 08 Dec 2019.

Vancouver:

Chang YT. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10919/83813.

Council of Science Editors:

Chang YT. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83813


King Abdullah University of Science and Technology

19. Hou, Siqing. Neural Inductive Matrix Completion for Predicting Disease-Gene Associations.

Degree: 2018, King Abdullah University of Science and Technology

 In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations, and side… (more)

Subjects/Keywords: disease-gene predictions; Neural network; matrix completion; genetic disorders; human phenotype ontology

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

APA (6th Edition):

Hou, S. (2018). Neural Inductive Matrix Completion for Predicting Disease-Gene Associations. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/627946

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):

Hou, Siqing. “Neural Inductive Matrix Completion for Predicting Disease-Gene Associations.” 2018. Thesis, King Abdullah University of Science and Technology. Accessed December 08, 2019. http://hdl.handle.net/10754/627946.

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

MLA Handbook (7th Edition):

Hou, Siqing. “Neural Inductive Matrix Completion for Predicting Disease-Gene Associations.” 2018. Web. 08 Dec 2019.

Vancouver:

Hou S. Neural Inductive Matrix Completion for Predicting Disease-Gene Associations. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10754/627946.

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

Council of Science Editors:

Hou S. Neural Inductive Matrix Completion for Predicting Disease-Gene Associations. [Thesis]. King Abdullah University of Science and Technology; 2018. Available from: http://hdl.handle.net/10754/627946

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


Georgia Tech

20. Zhou, Fan. Statistical inference for high dimensional data with low rank structure.

Degree: PhD, Mathematics, 2018, Georgia Tech

 We study two major topics on statistical inference for high dimensional data with low rank structure occurred in many machine learning and statistics applications. The… (more)

Subjects/Keywords: Nonparametric statistics; Matrix completion; Low rank; Nuclear norm; Tensor; Singular vector perturbation

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

APA (6th Edition):

Zhou, F. (2018). Statistical inference for high dimensional data with low rank structure. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60750

Chicago Manual of Style (16th Edition):

Zhou, Fan. “Statistical inference for high dimensional data with low rank structure.” 2018. Doctoral Dissertation, Georgia Tech. Accessed December 08, 2019. http://hdl.handle.net/1853/60750.

MLA Handbook (7th Edition):

Zhou, Fan. “Statistical inference for high dimensional data with low rank structure.” 2018. Web. 08 Dec 2019.

Vancouver:

Zhou F. Statistical inference for high dimensional data with low rank structure. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1853/60750.

Council of Science Editors:

Zhou F. Statistical inference for high dimensional data with low rank structure. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60750


University of New South Wales

21. Marjanovic, Goran. lq sparse signal estimation with applications.

Degree: Electrical Engineering & Telecommunications, 2012, University of New South Wales

 The use of sparsity has emerged in the last fifteen years as an important tool for solving many problems in the areas of signal processing… (more)

Subjects/Keywords: Inverse problems; Sparse; Non convex; Matrix completion; Inverse covariance; Linear regression; Penalized problem

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

APA (6th Edition):

Marjanovic, G. (2012). lq sparse signal estimation with applications. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/52400 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11073/SOURCE01?view=true

Chicago Manual of Style (16th Edition):

Marjanovic, Goran. “lq sparse signal estimation with applications.” 2012. Doctoral Dissertation, University of New South Wales. Accessed December 08, 2019. http://handle.unsw.edu.au/1959.4/52400 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11073/SOURCE01?view=true.

MLA Handbook (7th Edition):

Marjanovic, Goran. “lq sparse signal estimation with applications.” 2012. Web. 08 Dec 2019.

Vancouver:

Marjanovic G. lq sparse signal estimation with applications. [Internet] [Doctoral dissertation]. University of New South Wales; 2012. [cited 2019 Dec 08]. Available from: http://handle.unsw.edu.au/1959.4/52400 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11073/SOURCE01?view=true.

Council of Science Editors:

Marjanovic G. lq sparse signal estimation with applications. [Doctoral Dissertation]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/52400 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11073/SOURCE01?view=true

22. Zare, Armin. Low-complexity stochastic modeling of wall-bounded shear flows.

Degree: PhD, Electrical/Computer Engineering, 2016, University of Minnesota

 Turbulent flows are ubiquitous in nature and they appear in many engineering applications. Transition to turbulence, in general, increases skin-friction drag in air/water vehicles compromising… (more)

Subjects/Keywords: Control theory; Convex optimization; Flow Control; Structured matrix completion problems; Turbulence modeling; Turbulent flows

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

APA (6th Edition):

Zare, A. (2016). Low-complexity stochastic modeling of wall-bounded shear flows. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/185120

Chicago Manual of Style (16th Edition):

Zare, Armin. “Low-complexity stochastic modeling of wall-bounded shear flows.” 2016. Doctoral Dissertation, University of Minnesota. Accessed December 08, 2019. http://hdl.handle.net/11299/185120.

MLA Handbook (7th Edition):

Zare, Armin. “Low-complexity stochastic modeling of wall-bounded shear flows.” 2016. Web. 08 Dec 2019.

Vancouver:

Zare A. Low-complexity stochastic modeling of wall-bounded shear flows. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11299/185120.

Council of Science Editors:

Zare A. Low-complexity stochastic modeling of wall-bounded shear flows. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/185120


University of Minnesota

23. Ngo, Thanh Trung. Low dimensional approximations: problems and algorithms.

Degree: Computer Science, 2014, University of Minnesota

 High dimensional data usually have intrinsic low rank representations. These low rank representations not only reveal the hidden structure of the data but also reduce… (more)

Subjects/Keywords: Data analysis; Dimension reduction; Low dimensional approximation; Matrix completion; Numerical linear algebra; Optimization

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

APA (6th Edition):

Ngo, T. T. (2014). Low dimensional approximations: problems and algorithms. (Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/163875

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):

Ngo, Thanh Trung. “Low dimensional approximations: problems and algorithms.” 2014. Thesis, University of Minnesota. Accessed December 08, 2019. http://hdl.handle.net/11299/163875.

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

MLA Handbook (7th Edition):

Ngo, Thanh Trung. “Low dimensional approximations: problems and algorithms.” 2014. Web. 08 Dec 2019.

Vancouver:

Ngo TT. Low dimensional approximations: problems and algorithms. [Internet] [Thesis]. University of Minnesota; 2014. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/11299/163875.

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

Council of Science Editors:

Ngo TT. Low dimensional approximations: problems and algorithms. [Thesis]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/163875

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


Arizona State University

24. Krouse, Brian Richard. Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark.

Degree: MS, Computer Science, 2014, Arizona State University

 As the size and scope of valuable datasets has exploded across many industries and fields of research in recent years, an increasingly diverse audience has… (more)

Subjects/Keywords: Computer science; Artificial intelligence; Big Data; Hadoop; Machine Learning; Mahout; Matrix Completion; Spark

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

APA (6th Edition):

Krouse, B. R. (2014). Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/24857

Chicago Manual of Style (16th Edition):

Krouse, Brian Richard. “Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark.” 2014. Masters Thesis, Arizona State University. Accessed December 08, 2019. http://repository.asu.edu/items/24857.

MLA Handbook (7th Edition):

Krouse, Brian Richard. “Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark.” 2014. Web. 08 Dec 2019.

Vancouver:

Krouse BR. Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark. [Internet] [Masters thesis]. Arizona State University; 2014. [cited 2019 Dec 08]. Available from: http://repository.asu.edu/items/24857.

Council of Science Editors:

Krouse BR. Large-Scale Matrix Completion Using Orthogonal Rank-One Matrix Pursuit, Divide-Factor-Combine, and Apache Spark. [Masters Thesis]. Arizona State University; 2014. Available from: http://repository.asu.edu/items/24857


EPFL

25. Thanikachalam, Niranjan. Image Based Relighting of Cultural Artifacts.

Degree: 2016, EPFL

 By incorporating computational methods into the image acquisition pipeline, computational photography has opened up new avenues in the representation and visualization of real world objects… (more)

Subjects/Keywords: Inverse rendering; scene relighting; relightable photographs; stained glass windows; light transport matrix; compressive sensing; dictionary learning; matrix completion

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

APA (6th Edition):

Thanikachalam, N. (2016). Image Based Relighting of Cultural Artifacts. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/218529

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):

Thanikachalam, Niranjan. “Image Based Relighting of Cultural Artifacts.” 2016. Thesis, EPFL. Accessed December 08, 2019. http://infoscience.epfl.ch/record/218529.

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

MLA Handbook (7th Edition):

Thanikachalam, Niranjan. “Image Based Relighting of Cultural Artifacts.” 2016. Web. 08 Dec 2019.

Vancouver:

Thanikachalam N. Image Based Relighting of Cultural Artifacts. [Internet] [Thesis]. EPFL; 2016. [cited 2019 Dec 08]. Available from: http://infoscience.epfl.ch/record/218529.

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

Council of Science Editors:

Thanikachalam N. Image Based Relighting of Cultural Artifacts. [Thesis]. EPFL; 2016. Available from: http://infoscience.epfl.ch/record/218529

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


University of Oxford

26. Wei, Ke. Efficient algorithms for compressed sensing and matrix completion.

Degree: PhD, 2014, University of Oxford

 Compressed sensing and matrix completion are two new data acquisition techniques whose efficiency is achieved by exploring low dimensional structures in high dimensional data. Despite… (more)

Subjects/Keywords: 518; Numerical analysis; numerical algorithms; low per iteration complexity; hard thresholding; alternating minimization; compressed sensing; matrix completion

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

APA (6th Edition):

Wei, K. (2014). Efficient algorithms for compressed sensing and matrix completion. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:0e2e72fb-dd0c-457b-a0a5-f91c5212f5f5 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627829

Chicago Manual of Style (16th Edition):

Wei, Ke. “Efficient algorithms for compressed sensing and matrix completion.” 2014. Doctoral Dissertation, University of Oxford. Accessed December 08, 2019. http://ora.ox.ac.uk/objects/uuid:0e2e72fb-dd0c-457b-a0a5-f91c5212f5f5 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627829.

MLA Handbook (7th Edition):

Wei, Ke. “Efficient algorithms for compressed sensing and matrix completion.” 2014. Web. 08 Dec 2019.

Vancouver:

Wei K. Efficient algorithms for compressed sensing and matrix completion. [Internet] [Doctoral dissertation]. University of Oxford; 2014. [cited 2019 Dec 08]. Available from: http://ora.ox.ac.uk/objects/uuid:0e2e72fb-dd0c-457b-a0a5-f91c5212f5f5 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627829.

Council of Science Editors:

Wei K. Efficient algorithms for compressed sensing and matrix completion. [Doctoral Dissertation]. University of Oxford; 2014. Available from: http://ora.ox.ac.uk/objects/uuid:0e2e72fb-dd0c-457b-a0a5-f91c5212f5f5 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627829


EPFL

27. Kyrillidis, Anastasios. Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences.

Degree: 2014, EPFL

 Many natural and man-made signals can be described as having a few degrees of freedom relative to their size due to natural parameterizations or constraints;… (more)

Subjects/Keywords: Sparse Euclidean projections; sparse linear regression; compressed sensing; affine rank minimization; matrix completion; structured sparsity; convex composite minimization; self-concordance

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

APA (6th Edition):

Kyrillidis, A. (2014). Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/202053

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):

Kyrillidis, Anastasios. “Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences.” 2014. Thesis, EPFL. Accessed December 08, 2019. http://infoscience.epfl.ch/record/202053.

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

MLA Handbook (7th Edition):

Kyrillidis, Anastasios. “Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences.” 2014. Web. 08 Dec 2019.

Vancouver:

Kyrillidis A. Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences. [Internet] [Thesis]. EPFL; 2014. [cited 2019 Dec 08]. Available from: http://infoscience.epfl.ch/record/202053.

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

Council of Science Editors:

Kyrillidis A. Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences. [Thesis]. EPFL; 2014. Available from: http://infoscience.epfl.ch/record/202053

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


University of Lund

28. Grussler, Christian. Rank Reduction with Convex Constraints.

Degree: 2017, University of Lund

 This thesis addresses problems which require low-rank solutions under convex constraints. In particular, the focus lies on model reduction of positive systems, as well as… (more)

Subjects/Keywords: Reglerteknik; low-rank approximation; model reduction; non-convex optimization; Douglas-Rachford; matrix completion; overlapping norm; k-support norm; atomic norm

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

APA (6th Edition):

Grussler, C. (2017). Rank Reduction with Convex Constraints. (Doctoral Dissertation). University of Lund. Retrieved from http://lup.lub.lu.se/record/54cb814f-59fe-4bc9-a7ef-773cbcf06889 ; http://portal.research.lu.se/ws/files/19595129/Thesis.pdf

Chicago Manual of Style (16th Edition):

Grussler, Christian. “Rank Reduction with Convex Constraints.” 2017. Doctoral Dissertation, University of Lund. Accessed December 08, 2019. http://lup.lub.lu.se/record/54cb814f-59fe-4bc9-a7ef-773cbcf06889 ; http://portal.research.lu.se/ws/files/19595129/Thesis.pdf.

MLA Handbook (7th Edition):

Grussler, Christian. “Rank Reduction with Convex Constraints.” 2017. Web. 08 Dec 2019.

Vancouver:

Grussler C. Rank Reduction with Convex Constraints. [Internet] [Doctoral dissertation]. University of Lund; 2017. [cited 2019 Dec 08]. Available from: http://lup.lub.lu.se/record/54cb814f-59fe-4bc9-a7ef-773cbcf06889 ; http://portal.research.lu.se/ws/files/19595129/Thesis.pdf.

Council of Science Editors:

Grussler C. Rank Reduction with Convex Constraints. [Doctoral Dissertation]. University of Lund; 2017. Available from: http://lup.lub.lu.se/record/54cb814f-59fe-4bc9-a7ef-773cbcf06889 ; http://portal.research.lu.se/ws/files/19595129/Thesis.pdf

29. Lafond, Jean. Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels.

Degree: Docteur es, Mathématiques appliquées, 2016, Paris Saclay

Dans cette thèse nous nous intéressons aux méthodes de complétion de matrices de faible rang et étudions certains problèmes reliés. Un premier ensemble de résultats… (more)

Subjects/Keywords: Statistique en grande dimension; Complétion de matrice; Apprentissage à grande échelle; High dimension statistics; Matrix completion; Large scale optimization

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

APA (6th Edition):

Lafond, J. (2016). Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels. (Doctoral Dissertation). Paris Saclay. Retrieved from http://www.theses.fr/2016SACLT002

Chicago Manual of Style (16th Edition):

Lafond, Jean. “Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels.” 2016. Doctoral Dissertation, Paris Saclay. Accessed December 08, 2019. http://www.theses.fr/2016SACLT002.

MLA Handbook (7th Edition):

Lafond, Jean. “Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels.” 2016. Web. 08 Dec 2019.

Vancouver:

Lafond J. Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels. [Internet] [Doctoral dissertation]. Paris Saclay; 2016. [cited 2019 Dec 08]. Available from: http://www.theses.fr/2016SACLT002.

Council of Science Editors:

Lafond J. Matrix completion : statistical and computational aspects : Complétion de matrice : aspects statistiques et computationnels. [Doctoral Dissertation]. Paris Saclay; 2016. Available from: http://www.theses.fr/2016SACLT002


University of Waterloo

30. Krislock, Nathan. Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion.

Degree: 2010, University of Waterloo

 The main result of this thesis is the development of a theory of semidefinite facial reduction for the Euclidean distance matrix completion problem. Our key… (more)

Subjects/Keywords: Euclidean distance matrices; low-rank matrix completion; semidefinite relaxations; facial reduction; wireless sensor network localization; molecular conformation

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

APA (6th Edition):

Krislock, N. (2010). Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/5093

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):

Krislock, Nathan. “Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion.” 2010. Thesis, University of Waterloo. Accessed December 08, 2019. http://hdl.handle.net/10012/5093.

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

MLA Handbook (7th Edition):

Krislock, Nathan. “Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion.” 2010. Web. 08 Dec 2019.

Vancouver:

Krislock N. Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion. [Internet] [Thesis]. University of Waterloo; 2010. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10012/5093.

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

Council of Science Editors:

Krislock N. Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion. [Thesis]. University of Waterloo; 2010. Available from: http://hdl.handle.net/10012/5093

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

[1] [2] [3]

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