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You searched for subject:(matrix factorization). Showing records 1 – 30 of 294 total matches.

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Texas A&M University

1. Belsare, Aditya Sanjay. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.

Degree: MS, Computer Engineering, 2014, Texas A&M University

 Direct sparse solvers are traditionally known to be robust, yet difficult to parallelize. In the context of circuit simulators, they present an important bottleneck where… (more)

Subjects/Keywords: Sparse matrix solver; LU Factorization

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

APA (6th Edition):

Belsare, A. S. (2014). Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153210

Chicago Manual of Style (16th Edition):

Belsare, Aditya Sanjay. “Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.” 2014. Masters Thesis, Texas A&M University. Accessed April 10, 2021. http://hdl.handle.net/1969.1/153210.

MLA Handbook (7th Edition):

Belsare, Aditya Sanjay. “Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.” 2014. Web. 10 Apr 2021.

Vancouver:

Belsare AS. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. [Internet] [Masters thesis]. Texas A&M University; 2014. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/1969.1/153210.

Council of Science Editors:

Belsare AS. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. [Masters Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153210


Penn State University

2. Li, Yunhang. Matrix Factorization Method For Lagre Recommendation System.

Degree: 2015, Penn State University

 Recommendation system is a very popular topic in recent years. It’s very efficient to utilize machine learning algorithms to improve the performance of recommendation systems.… (more)

Subjects/Keywords: Recommendation system; Matrix Factorization

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APA (6th Edition):

Li, Y. (2015). Matrix Factorization Method For Lagre Recommendation System. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26488

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):

Li, Yunhang. “Matrix Factorization Method For Lagre Recommendation System.” 2015. Thesis, Penn State University. Accessed April 10, 2021. https://submit-etda.libraries.psu.edu/catalog/26488.

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

MLA Handbook (7th Edition):

Li, Yunhang. “Matrix Factorization Method For Lagre Recommendation System.” 2015. Web. 10 Apr 2021.

Vancouver:

Li Y. Matrix Factorization Method For Lagre Recommendation System. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Apr 10]. Available from: https://submit-etda.libraries.psu.edu/catalog/26488.

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

Council of Science Editors:

Li Y. Matrix Factorization Method For Lagre Recommendation System. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26488

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


University of New Mexico

3. Potluru, Vamsi. Matrix Factorization: Nonnegativity, Sparsity and Independence.

Degree: Department of Computer Science, 2014, University of New Mexico

Matrix factorization arises in a wide range of application domains and is useful for extracting the latent features in the dataset. Examples include recommender systems,… (more)

Subjects/Keywords: Matrix factorization; Nonnegativity; Sparsity; Independence

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APA (6th Edition):

Potluru, V. (2014). Matrix Factorization: Nonnegativity, Sparsity and Independence. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/24336

Chicago Manual of Style (16th Edition):

Potluru, Vamsi. “Matrix Factorization: Nonnegativity, Sparsity and Independence.” 2014. Doctoral Dissertation, University of New Mexico. Accessed April 10, 2021. http://hdl.handle.net/1928/24336.

MLA Handbook (7th Edition):

Potluru, Vamsi. “Matrix Factorization: Nonnegativity, Sparsity and Independence.” 2014. Web. 10 Apr 2021.

Vancouver:

Potluru V. Matrix Factorization: Nonnegativity, Sparsity and Independence. [Internet] [Doctoral dissertation]. University of New Mexico; 2014. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/1928/24336.

Council of Science Editors:

Potluru V. Matrix Factorization: Nonnegativity, Sparsity and Independence. [Doctoral Dissertation]. University of New Mexico; 2014. Available from: http://hdl.handle.net/1928/24336

4. -7585-6925. Distributed and dynamic factor modeling of online data.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Texas – Austin

 The domain of data mining and machine learning has expanded rapidly in recent years to include both large-scale distributed and streaming computation. Although many open-source… (more)

Subjects/Keywords: Distributed clustering; Dynamic clustering; Matrix factorization; Co-factorization

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APA (6th Edition):

-7585-6925. (2017). Distributed and dynamic factor modeling of online data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62065

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7585-6925. “Distributed and dynamic factor modeling of online data.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed April 10, 2021. http://hdl.handle.net/2152/62065.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7585-6925. “Distributed and dynamic factor modeling of online data.” 2017. Web. 10 Apr 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7585-6925. Distributed and dynamic factor modeling of online data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/2152/62065.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7585-6925. Distributed and dynamic factor modeling of online data. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62065

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


NSYSU

5. Chang, Cheng-Jui. Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization.

Degree: Master, Information Management, 2017, NSYSU

 This research proposes an approach to find the cuisines, the types of dishes, from the recipes, ingredients and methods of producing dishes. We believe that… (more)

Subjects/Keywords: clustering; network; recommendation; matrix factorization; text mining

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APA (6th Edition):

Chang, C. (2017). Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0812117-134940

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):

Chang, Cheng-Jui. “Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization.” 2017. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0812117-134940.

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

MLA Handbook (7th Edition):

Chang, Cheng-Jui. “Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization.” 2017. Web. 10 Apr 2021.

Vancouver:

Chang C. Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization. [Internet] [Thesis]. NSYSU; 2017. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0812117-134940.

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

Council of Science Editors:

Chang C. Cuisine Discovery based on Recipe-Ingredient Network and Matrix Factorization. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0812117-134940

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


Northeastern University

6. Wang, Yueyang. New initialization strategy for nonnegative matrix factorization.

Degree: MS, Department of Electrical and Computer Engineering, 2018, Northeastern University

 Nonnegative matrix factorization (NMF) has been proved to be a powerful data representa-tion method, and has shown success in applications such as data representation and… (more)

Subjects/Keywords: complementary elements; nonnegative matrix factorization; data

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APA (6th Edition):

Wang, Y. (2018). New initialization strategy for nonnegative matrix factorization. (Masters Thesis). Northeastern University. Retrieved from http://hdl.handle.net/2047/D20290549

Chicago Manual of Style (16th Edition):

Wang, Yueyang. “New initialization strategy for nonnegative matrix factorization.” 2018. Masters Thesis, Northeastern University. Accessed April 10, 2021. http://hdl.handle.net/2047/D20290549.

MLA Handbook (7th Edition):

Wang, Yueyang. “New initialization strategy for nonnegative matrix factorization.” 2018. Web. 10 Apr 2021.

Vancouver:

Wang Y. New initialization strategy for nonnegative matrix factorization. [Internet] [Masters thesis]. Northeastern University; 2018. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/2047/D20290549.

Council of Science Editors:

Wang Y. New initialization strategy for nonnegative matrix factorization. [Masters Thesis]. Northeastern University; 2018. Available from: http://hdl.handle.net/2047/D20290549


University of Minnesota

7. Mosesov, Artem. Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization.

Degree: M.S.E.E., Electrical Engineering, 2014, University of Minnesota

 Problems with non-negativity constrains have recently attracted a great deal of interest. Non-negativity constraints arise naturally in many applications, and are often necessary for proper… (more)

Subjects/Keywords: least squares; matrix factorization; NMF; NNLS; Nonnegative

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APA (6th Edition):

Mosesov, A. (2014). Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/173949

Chicago Manual of Style (16th Edition):

Mosesov, Artem. “Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization.” 2014. Masters Thesis, University of Minnesota. Accessed April 10, 2021. http://hdl.handle.net/11299/173949.

MLA Handbook (7th Edition):

Mosesov, Artem. “Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization.” 2014. Web. 10 Apr 2021.

Vancouver:

Mosesov A. Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization. [Internet] [Masters thesis]. University of Minnesota; 2014. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/11299/173949.

Council of Science Editors:

Mosesov A. Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization. [Masters Thesis]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/173949


University of New South Wales

8. Luo, Cheng. Temporal Dynamics in Recommender Systems.

Degree: Computer Science & Engineering, 2016, University of New South Wales

 In real-world scenarios, user preferences for items are constantly drifting over time as item perception and popularity are changing when new fashions or products emerge.… (more)

Subjects/Keywords: matrix factorization; recommender systems; temporal dynamics

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APA (6th Edition):

Luo, C. (2016). Temporal Dynamics in Recommender Systems. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55939 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39683/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Luo, Cheng. “Temporal Dynamics in Recommender Systems.” 2016. Doctoral Dissertation, University of New South Wales. Accessed April 10, 2021. http://handle.unsw.edu.au/1959.4/55939 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39683/SOURCE02?view=true.

MLA Handbook (7th Edition):

Luo, Cheng. “Temporal Dynamics in Recommender Systems.” 2016. Web. 10 Apr 2021.

Vancouver:

Luo C. Temporal Dynamics in Recommender Systems. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2021 Apr 10]. Available from: http://handle.unsw.edu.au/1959.4/55939 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39683/SOURCE02?view=true.

Council of Science Editors:

Luo C. Temporal Dynamics in Recommender Systems. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/55939 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39683/SOURCE02?view=true


University of Texas – Austin

9. Yu, Hsiang-Fu. Scalable algorithms for latent variable models in machine learning.

Degree: PhD, Computer science, 2016, University of Texas – Austin

 Latent variable modeling (LVM) is a popular approach in many machine learning applications, such as recommender systems and topic modeling, due to its ability to… (more)

Subjects/Keywords: Latent variable modeling; Matrix factorization; Algorithms; Data

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APA (6th Edition):

Yu, H. (2016). Scalable algorithms for latent variable models in machine learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41635

Chicago Manual of Style (16th Edition):

Yu, Hsiang-Fu. “Scalable algorithms for latent variable models in machine learning.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed April 10, 2021. http://hdl.handle.net/2152/41635.

MLA Handbook (7th Edition):

Yu, Hsiang-Fu. “Scalable algorithms for latent variable models in machine learning.” 2016. Web. 10 Apr 2021.

Vancouver:

Yu H. Scalable algorithms for latent variable models in machine learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/2152/41635.

Council of Science Editors:

Yu H. Scalable algorithms for latent variable models in machine learning. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41635


University of Cincinnati

10. Li, Kendrick T. Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting.

Degree: MS, Engineering and Applied Science: Computer Engineering, 2020, University of Cincinnati

 Functional magnetic resonance imaging (fMRI) data has been collected and studied in the neuroscience community for more than two decades. Methods have been developed to… (more)

Subjects/Keywords: Computer Science; fMRI; Functional connectivity; FC fingerprinting; Matrix tri-factorization; Group matrix tri-factorization

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APA (6th Edition):

Li, K. T. (2020). Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592136688034675

Chicago Manual of Style (16th Edition):

Li, Kendrick T. “Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting.” 2020. Masters Thesis, University of Cincinnati. Accessed April 10, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592136688034675.

MLA Handbook (7th Edition):

Li, Kendrick T. “Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting.” 2020. Web. 10 Apr 2021.

Vancouver:

Li KT. Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting. [Internet] [Masters thesis]. University of Cincinnati; 2020. [cited 2021 Apr 10]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592136688034675.

Council of Science Editors:

Li KT. Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting. [Masters Thesis]. University of Cincinnati; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592136688034675


University of Minnesota

11. 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 April 10, 2021. http://hdl.handle.net/11299/175344.

MLA Handbook (7th Edition):

Sun, Ruoyu. “Matrix Completion via Nonconvex Factorization: Algorithms and Theory.” 2015. Web. 10 Apr 2021.

Vancouver:

Sun R. Matrix Completion via Nonconvex Factorization: Algorithms and Theory. [Internet] [Doctoral dissertation]. University of Minnesota; 2015. [cited 2021 Apr 10]. 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 Technology, Sydney

12. Li, Fangfang. Incorporating couplings into collaborative filtering.

Degree: 2016, University of Technology, Sydney

 Recommender Systems (RS) have been proposed to help users tackle information overload by suggesting potentially interesting items to users. A typical RS usually has a… (more)

Subjects/Keywords: Recommender Systems (RS).; Collaborative Filtering (CF).; Hybrid Filtering.; Coupling.; Coupled user-based matrix factorization (CUMF).; Coupled item-based matrix factorization (CIMF).; Coupled matrix factorization (CMF).

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APA (6th Edition):

Li, F. (2016). Incorporating couplings into collaborative filtering. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/44174

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):

Li, Fangfang. “Incorporating couplings into collaborative filtering.” 2016. Thesis, University of Technology, Sydney. Accessed April 10, 2021. http://hdl.handle.net/10453/44174.

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

MLA Handbook (7th Edition):

Li, Fangfang. “Incorporating couplings into collaborative filtering.” 2016. Web. 10 Apr 2021.

Vancouver:

Li F. Incorporating couplings into collaborative filtering. [Internet] [Thesis]. University of Technology, Sydney; 2016. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10453/44174.

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

Council of Science Editors:

Li F. Incorporating couplings into collaborative filtering. [Thesis]. University of Technology, Sydney; 2016. Available from: http://hdl.handle.net/10453/44174

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


NSYSU

13. Yang, Wan-Chen. Topic Evolution Discovery based on Regularized Matrix Factorization.

Degree: Master, Information Management, 2018, NSYSU

 In this thesis, we propose Hierarchical Non-negative Matrix Factorization(hNMF) to discover the hierarchical correlation among topics. The topics in lower layers are more concrete, whereas… (more)

Subjects/Keywords: Topic model; Hierarchical model; Non-negative matrix factorization; Hierarchical Non-negative matrix factorization; Topic classification; Topic evolution discovery; Multi-layer topic

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APA (6th Edition):

Yang, W. (2018). Topic Evolution Discovery based on Regularized Matrix Factorization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727118-143310

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):

Yang, Wan-Chen. “Topic Evolution Discovery based on Regularized Matrix Factorization.” 2018. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727118-143310.

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

MLA Handbook (7th Edition):

Yang, Wan-Chen. “Topic Evolution Discovery based on Regularized Matrix Factorization.” 2018. Web. 10 Apr 2021.

Vancouver:

Yang W. Topic Evolution Discovery based on Regularized Matrix Factorization. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727118-143310.

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

Council of Science Editors:

Yang W. Topic Evolution Discovery based on Regularized Matrix Factorization. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727118-143310

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


University of South Africa

14. Gaoseb, Frans Otto. Spectral factorization of matrices .

Degree: 2020, University of South Africa

 The research will analyze and compare the current research on the spectral factorization of non-singular and singular matrices. We show that a nonsingular non-scalar matrix(more)

Subjects/Keywords: Spectral factorization; Matrix factorization; Singular Matrices; Non-singular matrices; Involutions; Commutators; Unipotent matrices; Positive-definite matrices; Hermitian factorization; Scalar matrices; Nilpotent factorization

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APA (6th Edition):

Gaoseb, F. O. (2020). Spectral factorization of matrices . (Masters Thesis). University of South Africa. Retrieved from http://hdl.handle.net/10500/26844

Chicago Manual of Style (16th Edition):

Gaoseb, Frans Otto. “Spectral factorization of matrices .” 2020. Masters Thesis, University of South Africa. Accessed April 10, 2021. http://hdl.handle.net/10500/26844.

MLA Handbook (7th Edition):

Gaoseb, Frans Otto. “Spectral factorization of matrices .” 2020. Web. 10 Apr 2021.

Vancouver:

Gaoseb FO. Spectral factorization of matrices . [Internet] [Masters thesis]. University of South Africa; 2020. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10500/26844.

Council of Science Editors:

Gaoseb FO. Spectral factorization of matrices . [Masters Thesis]. University of South Africa; 2020. Available from: http://hdl.handle.net/10500/26844


University of California – Irvine

15. 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 April 10, 2021. 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. 10 Apr 2021.

Vancouver:

Pezeshkpour P. Compact Factorization of Matrices Using Generalized Round-Rank. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2021 Apr 10]. 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

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

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 April 10, 2021. http://hdl.handle.net/11299/192686.

MLA Handbook (7th Edition):

Sharma, Mohit. “Preference modeling and Accuracy in Recommender Systems.” 2017. Web. 10 Apr 2021.

Vancouver:

Sharma M. Preference modeling and Accuracy in Recommender Systems. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2021 Apr 10]. 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


NSYSU

17. Ma, Chuan-yuan. Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation.

Degree: Master, Information Management, 2014, NSYSU

 It becomes a more and more popular approach to develop recommendation systems based on trust relationships on the social networks. While social information that explicitly… (more)

Subjects/Keywords: K-Nearest Neighbor; Trust Transitivity; Distrust; Matrix Factorization; In-Degree

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

APA (6th Edition):

Ma, C. (2014). Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-113648

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):

Ma, Chuan-yuan. “Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation.” 2014. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-113648.

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

MLA Handbook (7th Edition):

Ma, Chuan-yuan. “Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation.” 2014. Web. 10 Apr 2021.

Vancouver:

Ma C. Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-113648.

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

Council of Science Editors:

Ma C. Combining Co-Ratings and Trust Relationships on Social Networks for Collaborative Recommendation. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-113648

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


NSYSU

18. Tseng, Kuan-Yu. Context-aware Collaborative Filtering Methods for Multimedia Recommendation.

Degree: Master, Information Management, 2014, NSYSU

 The rapid development of mobile device and multimedia allows us today to have extremely rich multimedia information sources. The numbers of data also increase rapidly… (more)

Subjects/Keywords: Mobile Device; Collaborative Filtering; Matrix Factorization; Context-Awareness; Recommender System

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

APA (6th Edition):

Tseng, K. (2014). Context-aware Collaborative Filtering Methods for Multimedia Recommendation. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-122019

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):

Tseng, Kuan-Yu. “Context-aware Collaborative Filtering Methods for Multimedia Recommendation.” 2014. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-122019.

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

MLA Handbook (7th Edition):

Tseng, Kuan-Yu. “Context-aware Collaborative Filtering Methods for Multimedia Recommendation.” 2014. Web. 10 Apr 2021.

Vancouver:

Tseng K. Context-aware Collaborative Filtering Methods for Multimedia Recommendation. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-122019.

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

Council of Science Editors:

Tseng K. Context-aware Collaborative Filtering Methods for Multimedia Recommendation. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-122019

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


NSYSU

19. Hsieh, Sung-chen. Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials.

Degree: Master, Applied Mathematics, 2014, NSYSU

 Computing the greatest common divisor (GCD) of univariate polynomials is one of the fundamental algebraic problems with a long history. The classical Euclidean algorithm is… (more)

Subjects/Keywords: numerical nullity; polynomial; greatest common divisor; Sylvester matrix; QR-factorization

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

APA (6th Edition):

Hsieh, S. (2014). Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1117114-104741

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):

Hsieh, Sung-chen. “Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials.” 2014. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1117114-104741.

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

MLA Handbook (7th Edition):

Hsieh, Sung-chen. “Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials.” 2014. Web. 10 Apr 2021.

Vancouver:

Hsieh S. Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1117114-104741.

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

Council of Science Editors:

Hsieh S. Computing the Numerical Nullity of Sylvester Matrix of Univariate Polynomials. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1117114-104741

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


NSYSU

20. Yang, Tsung-Lin. Combining Trust Relationships and Super Users for Collaborative Recommendation.

Degree: Master, Information Management, 2017, NSYSU

 The network and mobile communication develop very quickly in recent years. We could get the data easily online. However, the speed of data transformation is… (more)

Subjects/Keywords: Collaborative Filtering; Recommendation System; Cold Start; Matrix Factorization; Trust

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

APA (6th Edition):

Yang, T. (2017). Combining Trust Relationships and Super Users for Collaborative Recommendation. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0113117-153742

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):

Yang, Tsung-Lin. “Combining Trust Relationships and Super Users for Collaborative Recommendation.” 2017. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0113117-153742.

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

MLA Handbook (7th Edition):

Yang, Tsung-Lin. “Combining Trust Relationships and Super Users for Collaborative Recommendation.” 2017. Web. 10 Apr 2021.

Vancouver:

Yang T. Combining Trust Relationships and Super Users for Collaborative Recommendation. [Internet] [Thesis]. NSYSU; 2017. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0113117-153742.

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

Council of Science Editors:

Yang T. Combining Trust Relationships and Super Users for Collaborative Recommendation. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0113117-153742

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


NSYSU

21. Wang, Shih-hao. Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set.

Degree: Master, Information Management, 2017, NSYSU

 There are two types of methods often used to develop collaborative recommender systems. One is based on the similarity calculation and the other is based… (more)

Subjects/Keywords: Context Aware; Matrix Factorization; Cloud Computing; Recommended System; Collaborative Filtering

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

APA (6th Edition):

Wang, S. (2017). Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0221117-203746

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, Shih-hao. “Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set.” 2017. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0221117-203746.

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

MLA Handbook (7th Edition):

Wang, Shih-hao. “Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set.” 2017. Web. 10 Apr 2021.

Vancouver:

Wang S. Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set. [Internet] [Thesis]. NSYSU; 2017. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0221117-203746.

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

Council of Science Editors:

Wang S. Using Cloud Computing to Improve the Efficiency and Effectiveness of Matrix Factorization : A Case Study of Context-aware Data Set. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0221117-203746

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


Dalhousie University

22. Toganassova, Dilyara. SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA.

Degree: Master of Applied Science, Department of Environmental Engineering, 2013, Dalhousie University

 This study investigated the source attribution of ship emissions to atmospheric particulate matter with a median aerodynamic diameter less than, or equal to 2.5 micron… (more)

Subjects/Keywords: Source apportionment; PM2.5; USEPA Positive Matrix Factorization; sources (factors)

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

APA (6th Edition):

Toganassova, D. (2013). SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA. (Masters Thesis). Dalhousie University. Retrieved from http://hdl.handle.net/10222/21432

Chicago Manual of Style (16th Edition):

Toganassova, Dilyara. “SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA.” 2013. Masters Thesis, Dalhousie University. Accessed April 10, 2021. http://hdl.handle.net/10222/21432.

MLA Handbook (7th Edition):

Toganassova, Dilyara. “SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA.” 2013. Web. 10 Apr 2021.

Vancouver:

Toganassova D. SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA. [Internet] [Masters thesis]. Dalhousie University; 2013. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10222/21432.

Council of Science Editors:

Toganassova D. SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA. [Masters Thesis]. Dalhousie University; 2013. Available from: http://hdl.handle.net/10222/21432


San Jose State University

23. Gulati, Avni. Social Recommendation Systems.

Degree: MS, Computer Engineering, 2018, San Jose State University

  In recent years, with the rise of online social networks, personalized recommendations that leverage the aspect of social connections have become a very intriguing… (more)

Subjects/Keywords: influence propagation; matrix factorization; recommendation system; social network; social regularization

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APA (6th Edition):

Gulati, A. (2018). Social Recommendation Systems. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.6z86-4w3x ; https://scholarworks.sjsu.edu/etd_theses/4968

Chicago Manual of Style (16th Edition):

Gulati, Avni. “Social Recommendation Systems.” 2018. Masters Thesis, San Jose State University. Accessed April 10, 2021. https://doi.org/10.31979/etd.6z86-4w3x ; https://scholarworks.sjsu.edu/etd_theses/4968.

MLA Handbook (7th Edition):

Gulati, Avni. “Social Recommendation Systems.” 2018. Web. 10 Apr 2021.

Vancouver:

Gulati A. Social Recommendation Systems. [Internet] [Masters thesis]. San Jose State University; 2018. [cited 2021 Apr 10]. Available from: https://doi.org/10.31979/etd.6z86-4w3x ; https://scholarworks.sjsu.edu/etd_theses/4968.

Council of Science Editors:

Gulati A. Social Recommendation Systems. [Masters Thesis]. San Jose State University; 2018. Available from: https://doi.org/10.31979/etd.6z86-4w3x ; https://scholarworks.sjsu.edu/etd_theses/4968


University of Alberta

24. Liu, Bang. Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction.

Degree: MS, Department of Electrical and Computer Engineering, 2015, University of Alberta

 In this thesis, I study the application of matrix and tensor approximation techniques to Internet latency prediction and purchase prediction in e-commerce. Traditional approaches for… (more)

Subjects/Keywords: Network Latency Prediction; Online Purchase Prediction; Matrix Factorization

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

APA (6th Edition):

Liu, B. (2015). Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/zw12z797h

Chicago Manual of Style (16th Edition):

Liu, Bang. “Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction.” 2015. Masters Thesis, University of Alberta. Accessed April 10, 2021. https://era.library.ualberta.ca/files/zw12z797h.

MLA Handbook (7th Edition):

Liu, Bang. “Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction.” 2015. Web. 10 Apr 2021.

Vancouver:

Liu B. Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2021 Apr 10]. Available from: https://era.library.ualberta.ca/files/zw12z797h.

Council of Science Editors:

Liu B. Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/zw12z797h


NSYSU

25. Ku, Che-wen. Topic Recommendation and Discovery based on Matrix Factorization.

Degree: Master, Information Management, 2017, NSYSU

 Nowadays, there are more and more text documents on the Internet with the development of the Internet, because much information is related to text. Thus,… (more)

Subjects/Keywords: Non-negative Matrix Factorization; Topic Discovery; Recommendation; Topic Modeling

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

APA (6th Edition):

Ku, C. (2017). Topic Recommendation and Discovery based on Matrix Factorization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-145750

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):

Ku, Che-wen. “Topic Recommendation and Discovery based on Matrix Factorization.” 2017. Thesis, NSYSU. Accessed April 10, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-145750.

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

MLA Handbook (7th Edition):

Ku, Che-wen. “Topic Recommendation and Discovery based on Matrix Factorization.” 2017. Web. 10 Apr 2021.

Vancouver:

Ku C. Topic Recommendation and Discovery based on Matrix Factorization. [Internet] [Thesis]. NSYSU; 2017. [cited 2021 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-145750.

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

Council of Science Editors:

Ku C. Topic Recommendation and Discovery based on Matrix Factorization. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-145750

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


Purdue University

26. Kang, Jisun. Improving a mesh segmentation algorithm based on non-negative matrix factorization.

Degree: MS, Computer Graphics Technology, 2016, Purdue University

  3D Mesh segmentation is used in various applications such as object recognition, reconstruction, and analyzing structure of meshes. The method for 3D mesh segmentation… (more)

Subjects/Keywords: Applied sciences; Mesh segmentation; Non-negative matrix factorization; Computer Sciences

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APA (6th Edition):

Kang, J. (2016). Improving a mesh segmentation algorithm based on non-negative matrix factorization. (Thesis). Purdue University. Retrieved from https://docs.lib.purdue.edu/open_access_theses/861

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):

Kang, Jisun. “Improving a mesh segmentation algorithm based on non-negative matrix factorization.” 2016. Thesis, Purdue University. Accessed April 10, 2021. https://docs.lib.purdue.edu/open_access_theses/861.

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

MLA Handbook (7th Edition):

Kang, Jisun. “Improving a mesh segmentation algorithm based on non-negative matrix factorization.” 2016. Web. 10 Apr 2021.

Vancouver:

Kang J. Improving a mesh segmentation algorithm based on non-negative matrix factorization. [Internet] [Thesis]. Purdue University; 2016. [cited 2021 Apr 10]. Available from: https://docs.lib.purdue.edu/open_access_theses/861.

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

Council of Science Editors:

Kang J. Improving a mesh segmentation algorithm based on non-negative matrix factorization. [Thesis]. Purdue University; 2016. Available from: https://docs.lib.purdue.edu/open_access_theses/861

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


Universidade Nova

27. Dias, Pedro Ricardo Gomes. Recommending media content based on machine learning methods.

Degree: 2011, Universidade Nova

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Information is nowadays made available and consumed faster than ever before. This information technology generation… (more)

Subjects/Keywords: Recommender systems; Collaborative filtering; Matrix factorization; Groupbased recommendations; Interactive TV

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APA (6th Edition):

Dias, P. R. G. (2011). Recommending media content based on machine learning methods. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/6581

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):

Dias, Pedro Ricardo Gomes. “Recommending media content based on machine learning methods.” 2011. Thesis, Universidade Nova. Accessed April 10, 2021. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/6581.

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

MLA Handbook (7th Edition):

Dias, Pedro Ricardo Gomes. “Recommending media content based on machine learning methods.” 2011. Web. 10 Apr 2021.

Vancouver:

Dias PRG. Recommending media content based on machine learning methods. [Internet] [Thesis]. Universidade Nova; 2011. [cited 2021 Apr 10]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/6581.

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

Council of Science Editors:

Dias PRG. Recommending media content based on machine learning methods. [Thesis]. Universidade Nova; 2011. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/6581

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

28. Heß, Sibylle Charlotte. A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints.

Degree: 2018, Technische Universität Dortmund

 One of the first and most fundamental tasks in machine learning is to group observations within a dataset. Given a notion of similarity, finding those… (more)

Subjects/Keywords: Matrix factorization; Binary optimization; Clustering; 004; Matrizenzerlegung; Boolesche Optimierung; Cluster-Analyse

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

APA (6th Edition):

Heß, S. C. (2018). A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints. (Doctoral Dissertation). Technische Universität Dortmund. Retrieved from http://dx.doi.org/10.17877/DE290R-20240

Chicago Manual of Style (16th Edition):

Heß, Sibylle Charlotte. “A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints.” 2018. Doctoral Dissertation, Technische Universität Dortmund. Accessed April 10, 2021. http://dx.doi.org/10.17877/DE290R-20240.

MLA Handbook (7th Edition):

Heß, Sibylle Charlotte. “A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints.” 2018. Web. 10 Apr 2021.

Vancouver:

Heß SC. A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints. [Internet] [Doctoral dissertation]. Technische Universität Dortmund; 2018. [cited 2021 Apr 10]. Available from: http://dx.doi.org/10.17877/DE290R-20240.

Council of Science Editors:

Heß SC. A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints. [Doctoral Dissertation]. Technische Universität Dortmund; 2018. Available from: http://dx.doi.org/10.17877/DE290R-20240


University of Ontario Institute of Technology

29. Shanks, Ryan A. Towards parallax-based unencumbered displays.

Degree: 2015, University of Ontario Institute of Technology

 We present an analysis of content adaptive parallax barriers used for multi-layer unencumbered displays. We explain the techniques involved in detail from the input light… (more)

Subjects/Keywords: Computational displays; Content adaptive parallax barriers; Non-negative matrix factorization; Autostereoscopic

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

APA (6th Edition):

Shanks, R. A. (2015). Towards parallax-based unencumbered displays. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/620

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):

Shanks, Ryan A. “Towards parallax-based unencumbered displays.” 2015. Thesis, University of Ontario Institute of Technology. Accessed April 10, 2021. http://hdl.handle.net/10155/620.

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

MLA Handbook (7th Edition):

Shanks, Ryan A. “Towards parallax-based unencumbered displays.” 2015. Web. 10 Apr 2021.

Vancouver:

Shanks RA. Towards parallax-based unencumbered displays. [Internet] [Thesis]. University of Ontario Institute of Technology; 2015. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10155/620.

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

Council of Science Editors:

Shanks RA. Towards parallax-based unencumbered displays. [Thesis]. University of Ontario Institute of Technology; 2015. Available from: http://hdl.handle.net/10155/620

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


University of Ottawa

30. Agagu, Tosin. Recommendation Approaches Using Context-Aware Coupled Matrix Factorization .

Degree: 2017, University of Ottawa

 In general, recommender systems attempt to estimate user preference based on historical data. A context-aware recommender system attempts to generate better recommendations using contextual information.… (more)

Subjects/Keywords: Context-aware recommender system; Coupled matrix factorization; Recommendations; Context

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

APA (6th Edition):

Agagu, T. (2017). Recommendation Approaches Using Context-Aware Coupled Matrix Factorization . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/37012

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):

Agagu, Tosin. “Recommendation Approaches Using Context-Aware Coupled Matrix Factorization .” 2017. Thesis, University of Ottawa. Accessed April 10, 2021. http://hdl.handle.net/10393/37012.

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

MLA Handbook (7th Edition):

Agagu, Tosin. “Recommendation Approaches Using Context-Aware Coupled Matrix Factorization .” 2017. Web. 10 Apr 2021.

Vancouver:

Agagu T. Recommendation Approaches Using Context-Aware Coupled Matrix Factorization . [Internet] [Thesis]. University of Ottawa; 2017. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10393/37012.

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

Council of Science Editors:

Agagu T. Recommendation Approaches Using Context-Aware Coupled Matrix Factorization . [Thesis]. University of Ottawa; 2017. Available from: http://hdl.handle.net/10393/37012

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

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