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You searched for +publisher:"University of Texas – Austin" +contributor:("Ghosh, Joydeep"). Showing records 1 – 30 of 80 total matches.

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University of Texas – Austin

1. Park, Yubin. Privacy-aware publication and utilization of healthcare data.

Degree: Electrical and Computer Engineering, 2014, University of Texas – Austin

 Open access to health data can bring enormous social and economical benefits. However, such access can also lead to privacy breaches, which may result in… (more)

Subjects/Keywords: Data privacy; Healthcare

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

APA (6th Edition):

Park, Y. (2014). Privacy-aware publication and utilization of healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26932

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):

Park, Yubin. “Privacy-aware publication and utilization of healthcare data.” 2014. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/26932.

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

MLA Handbook (7th Edition):

Park, Yubin. “Privacy-aware publication and utilization of healthcare data.” 2014. Web. 25 Apr 2019.

Vancouver:

Park Y. Privacy-aware publication and utilization of healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/26932.

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

Council of Science Editors:

Park Y. Privacy-aware publication and utilization of healthcare data. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/26932

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


University of Texas – Austin

2. Bansal, Puneet, active 21st century. Analysis and classification of drift susceptible chemosensory responses.

Degree: Electrical and Computer Engineering, 2014, University of Texas – Austin

 This report presents machine learning models that can accurately classify gases by analyzing data from an array of 16 sensors. More specifically, the report presents… (more)

Subjects/Keywords: Ensemble classifier; Gas sensor

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APA (6th Edition):

Bansal, Puneet, a. 2. c. (2014). Analysis and classification of drift susceptible chemosensory responses. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/28532

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):

Bansal, Puneet, active 21st century. “Analysis and classification of drift susceptible chemosensory responses.” 2014. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/28532.

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

MLA Handbook (7th Edition):

Bansal, Puneet, active 21st century. “Analysis and classification of drift susceptible chemosensory responses.” 2014. Web. 25 Apr 2019.

Vancouver:

Bansal, Puneet a2c. Analysis and classification of drift susceptible chemosensory responses. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/28532.

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

Council of Science Editors:

Bansal, Puneet a2c. Analysis and classification of drift susceptible chemosensory responses. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/28532

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


University of Texas – Austin

3. Kumar, Abhimanu. Supervised language models for temporal resolution of text in absence of explicit temporal cues.

Degree: Computer Sciences, 2013, University of Texas – Austin

 This thesis explores the temporal analysis of text using the implicit temporal cues present in document. We consider the case when all explicit temporal expressions… (more)

Subjects/Keywords: Supervised language models; Temporal resolution; Temporal cues; Information retrieval

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APA (6th Edition):

Kumar, A. (2013). Supervised language models for temporal resolution of text in absence of explicit temporal cues. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/23581

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):

Kumar, Abhimanu. “Supervised language models for temporal resolution of text in absence of explicit temporal cues.” 2013. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/23581.

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

MLA Handbook (7th Edition):

Kumar, Abhimanu. “Supervised language models for temporal resolution of text in absence of explicit temporal cues.” 2013. Web. 25 Apr 2019.

Vancouver:

Kumar A. Supervised language models for temporal resolution of text in absence of explicit temporal cues. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/23581.

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

Council of Science Editors:

Kumar A. Supervised language models for temporal resolution of text in absence of explicit temporal cues. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/23581

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


University of Texas – Austin

4. Qian, Cheng. Classification of encrypted cloud computing service traffic using data mining techniques.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 In addition to the wireless network providers’ need for traffic classification, the need is more and more common in the Cloud Computing environment. A data… (more)

Subjects/Keywords: Internet traffic classification; Data mining; Cloud computing

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

APA (6th Edition):

Qian, C. (2011). Classification of encrypted cloud computing service traffic using data mining techniques. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4836

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):

Qian, Cheng. “Classification of encrypted cloud computing service traffic using data mining techniques.” 2011. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2011-12-4836.

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

MLA Handbook (7th Edition):

Qian, Cheng. “Classification of encrypted cloud computing service traffic using data mining techniques.” 2011. Web. 25 Apr 2019.

Vancouver:

Qian C. Classification of encrypted cloud computing service traffic using data mining techniques. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4836.

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

Council of Science Editors:

Qian C. Classification of encrypted cloud computing service traffic using data mining techniques. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4836

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


University of Texas – Austin

5. Edwards, James Adrian. Quantifying the multi-user account problem for collaborative filtering based recommender systems.

Degree: Electrical and Computer Engineering, 2009, University of Texas – Austin

 Identification based recommender systems make no distinction between users and accounts; all the data collected during account sessions are attributed to a single user. In… (more)

Subjects/Keywords: Recommender systems; Collaborative filtering; Multi-user accounts

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APA (6th Edition):

Edwards, J. A. (2009). Quantifying the multi-user account problem for collaborative filtering based recommender systems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-12-460

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):

Edwards, James Adrian. “Quantifying the multi-user account problem for collaborative filtering based recommender systems.” 2009. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2009-12-460.

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

MLA Handbook (7th Edition):

Edwards, James Adrian. “Quantifying the multi-user account problem for collaborative filtering based recommender systems.” 2009. Web. 25 Apr 2019.

Vancouver:

Edwards JA. Quantifying the multi-user account problem for collaborative filtering based recommender systems. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-460.

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

Council of Science Editors:

Edwards JA. Quantifying the multi-user account problem for collaborative filtering based recommender systems. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-460

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


University of Texas – Austin

6. Daruru, Srivatsava. Dataflow parallelism for large scale data mining.

Degree: Computer Sciences, 2010, University of Texas – Austin

 The unprecedented and exponential growth of data along with the advent of multi-core processors has triggered a massive paradigm shift from traditional single threaded programming… (more)

Subjects/Keywords: Dataflow processing; Data mining; Distributed computing; Large scale data mining; Parallel processing

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APA (6th Edition):

Daruru, S. (2010). Dataflow parallelism for large scale data mining. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1838

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):

Daruru, Srivatsava. “Dataflow parallelism for large scale data mining.” 2010. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1838.

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

MLA Handbook (7th Edition):

Daruru, Srivatsava. “Dataflow parallelism for large scale data mining.” 2010. Web. 25 Apr 2019.

Vancouver:

Daruru S. Dataflow parallelism for large scale data mining. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1838.

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

Council of Science Editors:

Daruru S. Dataflow parallelism for large scale data mining. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1838

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


University of Texas – Austin

7. Phuc, Nguyen Vinh, 1955-. The application of machine learning methods in software verification and validation.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Machine learning methods have been employed in data mining to discover useful, valid, and beneficial patterns for various applications of which, the domain encompasses areas… (more)

Subjects/Keywords: Machine learning; Software verification; Software validation; Algorithm; Decision tree; Category-partitioning

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APA (6th Edition):

Phuc, Nguyen Vinh, 1. (2010). The application of machine learning methods in software verification and validation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1605

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):

Phuc, Nguyen Vinh, 1955-. “The application of machine learning methods in software verification and validation.” 2010. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1605.

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

MLA Handbook (7th Edition):

Phuc, Nguyen Vinh, 1955-. “The application of machine learning methods in software verification and validation.” 2010. Web. 25 Apr 2019.

Vancouver:

Phuc, Nguyen Vinh 1. The application of machine learning methods in software verification and validation. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1605.

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

Council of Science Editors:

Phuc, Nguyen Vinh 1. The application of machine learning methods in software verification and validation. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1605

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


University of Texas – Austin

8. Huang, Hsiu-Min Chang, 1958-. Training experience satisfaction prediction based on trainees' general information.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Training is a powerful and required method to equip human resources with tools to keep their organizations competitive in the markets. Typically at the end… (more)

Subjects/Keywords: Data mining; Least squares regression; Training satisfaction prediction; Prediction quality; Training satisfaction factors; Software measurement; Models; Training evaluation methods

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

APA (6th Edition):

Huang, Hsiu-Min Chang, 1. (2010). Training experience satisfaction prediction based on trainees' general information. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1656

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):

Huang, Hsiu-Min Chang, 1958-. “Training experience satisfaction prediction based on trainees' general information.” 2010. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1656.

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

MLA Handbook (7th Edition):

Huang, Hsiu-Min Chang, 1958-. “Training experience satisfaction prediction based on trainees' general information.” 2010. Web. 25 Apr 2019.

Vancouver:

Huang, Hsiu-Min Chang 1. Training experience satisfaction prediction based on trainees' general information. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1656.

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

Council of Science Editors:

Huang, Hsiu-Min Chang 1. Training experience satisfaction prediction based on trainees' general information. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1656

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


University of Texas – Austin

9. Weber, Robert Arthur, 1983-. Analysis of storing wind energy for periods of seconds to hours in ERCOT.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Wind energy has dramatically changed the energy portfolio of Texas and more specifically, a region covering 75% of the state designated as ERCOT (Electric Reliability… (more)

Subjects/Keywords: ERCOT; Electric Reliability Council of Texas; Wind energy storage; Wind energy; Electricity prices; Utility prices; Texas

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APA (6th Edition):

Weber, Robert Arthur, 1. (2010). Analysis of storing wind energy for periods of seconds to hours in ERCOT. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1820

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):

Weber, Robert Arthur, 1983-. “Analysis of storing wind energy for periods of seconds to hours in ERCOT.” 2010. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1820.

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

MLA Handbook (7th Edition):

Weber, Robert Arthur, 1983-. “Analysis of storing wind energy for periods of seconds to hours in ERCOT.” 2010. Web. 25 Apr 2019.

Vancouver:

Weber, Robert Arthur 1. Analysis of storing wind energy for periods of seconds to hours in ERCOT. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1820.

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

Council of Science Editors:

Weber, Robert Arthur 1. Analysis of storing wind energy for periods of seconds to hours in ERCOT. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1820

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


University of Texas – Austin

10. Anderson, Dylan Zachary. Supervised gamma process Poisson factorization.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 This thesis develops the supervised gamma process Poisson factorization (S-GPPF) framework, a novel supervised topic model for joint modeling of count matrices and document labels.… (more)

Subjects/Keywords: Supervised topic modeling; Bayesian nonparametric; Gamma process; Poisson factorization

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APA (6th Edition):

Anderson, D. Z. (2015). Supervised gamma process Poisson factorization. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31866

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):

Anderson, Dylan Zachary. “Supervised gamma process Poisson factorization.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/31866.

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

MLA Handbook (7th Edition):

Anderson, Dylan Zachary. “Supervised gamma process Poisson factorization.” 2015. Web. 25 Apr 2019.

Vancouver:

Anderson DZ. Supervised gamma process Poisson factorization. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/31866.

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

Council of Science Editors:

Anderson DZ. Supervised gamma process Poisson factorization. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31866

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


University of Texas – Austin

11. Box, Timothy Andrew, 1982-. Swapbeat.com: a streaming, adaptive music service in the browser.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 In recent years, ongoing shifts in the economics of the music industry have driven many artists to reevaluate how they intend to make money, with… (more)

Subjects/Keywords: SoundCloud; Music streaming; JavaScript; Web crawling

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APA (6th Edition):

Box, Timothy Andrew, 1. (2015). Swapbeat.com: a streaming, adaptive music service in the browser. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/35323

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):

Box, Timothy Andrew, 1982-. “Swapbeat.com: a streaming, adaptive music service in the browser.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/35323.

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

MLA Handbook (7th Edition):

Box, Timothy Andrew, 1982-. “Swapbeat.com: a streaming, adaptive music service in the browser.” 2015. Web. 25 Apr 2019.

Vancouver:

Box, Timothy Andrew 1. Swapbeat.com: a streaming, adaptive music service in the browser. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/35323.

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

Council of Science Editors:

Box, Timothy Andrew 1. Swapbeat.com: a streaming, adaptive music service in the browser. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/35323

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


University of Texas – Austin

12. Sudan, Nikita Maple. Using social network information in recommender systems.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 Recommender Systems are used to select online information relevant to a given user. Traditional (memory based) recommenders explore the user-item rating matrix and make recommendations… (more)

Subjects/Keywords: Social networks; Trust; Recommender systems; Rating prediction; Co-clustering; Label propagation

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APA (6th Edition):

Sudan, N. M. (2011). Using social network information in recommender systems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-08-3855

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):

Sudan, Nikita Maple. “Using social network information in recommender systems.” 2011. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2011-08-3855.

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

MLA Handbook (7th Edition):

Sudan, Nikita Maple. “Using social network information in recommender systems.” 2011. Web. 25 Apr 2019.

Vancouver:

Sudan NM. Using social network information in recommender systems. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-3855.

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

Council of Science Editors:

Sudan NM. Using social network information in recommender systems. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-3855

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


University of Texas – Austin

13. Li, Xiaoqian. Structural equation modeling of political discussion networks.

Degree: Statistics, 2017, University of Texas – Austin

 This study conducts structural equation modeling (SEM) of political discussion networks. It examines multiple relationships between political discussion networks—network size and non-kin composition, political efficacy,… (more)

Subjects/Keywords: Structural equation modeling; Categorical variable

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APA (6th Edition):

Li, X. (2017). Structural equation modeling of political discussion networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62804

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, Xiaoqian. “Structural equation modeling of political discussion networks.” 2017. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/62804.

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

MLA Handbook (7th Edition):

Li, Xiaoqian. “Structural equation modeling of political discussion networks.” 2017. Web. 25 Apr 2019.

Vancouver:

Li X. Structural equation modeling of political discussion networks. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/62804.

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

Council of Science Editors:

Li X. Structural equation modeling of political discussion networks. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62804

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


University of Texas – Austin

14. -7421-5165. Topic modeling via scatter/gather clustering.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 Latent variable models such as Latent Dirichlet Allocation provide rich tools for analyzing large document corpora. They can uncover a wide range of hidden information… (more)

Subjects/Keywords: Topic model; Scatter; Gather; Clustering; Browsing; Latent dirichlet allocation

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APA (6th Edition):

-7421-5165. (2015). Topic modeling via scatter/gather clustering. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32316

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

Chicago Manual of Style (16th Edition):

-7421-5165. “Topic modeling via scatter/gather clustering.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/32316.

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

MLA Handbook (7th Edition):

-7421-5165. “Topic modeling via scatter/gather clustering.” 2015. Web. 25 Apr 2019.

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

Vancouver:

-7421-5165. Topic modeling via scatter/gather clustering. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/32316.

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

Council of Science Editors:

-7421-5165. Topic modeling via scatter/gather clustering. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32316

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


University of Texas – Austin

15. -4895-7744. A closed-form correlation model of oriented bandpass natural images beyond adjacent responses.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 Building natural scene statistical models is crucial for a large set of applications starting from the design of faithful image and video quality metrics to… (more)

Subjects/Keywords: Natural scene statistics; Bandpass natural images; Bivariate correlation models

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APA (6th Edition):

-4895-7744. (2015). A closed-form correlation model of oriented bandpass natural images beyond adjacent responses. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32315

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

Chicago Manual of Style (16th Edition):

-4895-7744. “A closed-form correlation model of oriented bandpass natural images beyond adjacent responses.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/32315.

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

MLA Handbook (7th Edition):

-4895-7744. “A closed-form correlation model of oriented bandpass natural images beyond adjacent responses.” 2015. Web. 25 Apr 2019.

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

Vancouver:

-4895-7744. A closed-form correlation model of oriented bandpass natural images beyond adjacent responses. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/32315.

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

Council of Science Editors:

-4895-7744. A closed-form correlation model of oriented bandpass natural images beyond adjacent responses. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32315

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


University of Texas – Austin

16. -5294-4228. Scalable smoothing algorithms for massive graph-structured data.

Degree: Computer Sciences, 2017, University of Texas – Austin

 Probabilistically modeling noisy data is a crucial step in virtually all scientific experiments and engineering pipelines. Recent years have seen the rise of several high-throughput… (more)

Subjects/Keywords: Smoothing; Algorithms; False discovery rate; Spatial smoothing; Total variation; Trend filtering

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APA (6th Edition):

-5294-4228. (2017). Scalable smoothing algorithms for massive graph-structured data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61823

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

Chicago Manual of Style (16th Edition):

-5294-4228. “Scalable smoothing algorithms for massive graph-structured data.” 2017. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/61823.

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

MLA Handbook (7th Edition):

-5294-4228. “Scalable smoothing algorithms for massive graph-structured data.” 2017. Web. 25 Apr 2019.

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

Vancouver:

-5294-4228. Scalable smoothing algorithms for massive graph-structured data. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/61823.

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

Council of Science Editors:

-5294-4228. Scalable smoothing algorithms for massive graph-structured data. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61823

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


University of Texas – Austin

17. -3562-6540. Learning and validating clinically meaningful phenotypes from electronic health data.

Degree: Computational Science, Engineering, and Mathematics, 2018, University of Texas – Austin

 The ever-growing adoption of electronic health records (EHR) to record patients' health journeys has resulted in vast amounts of heterogeneous, complex, and unwieldy information [Hripcsak… (more)

Subjects/Keywords: Computational phenotyping; Tensor factorization; Machine learning; Medical informatics; Model output validation

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APA (6th Edition):

-3562-6540. (2018). Learning and validating clinically meaningful phenotypes from electronic health data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/69179

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

Chicago Manual of Style (16th Edition):

-3562-6540. “Learning and validating clinically meaningful phenotypes from electronic health data.” 2018. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/69179.

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

MLA Handbook (7th Edition):

-3562-6540. “Learning and validating clinically meaningful phenotypes from electronic health data.” 2018. Web. 25 Apr 2019.

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

Vancouver:

-3562-6540. Learning and validating clinically meaningful phenotypes from electronic health data. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/69179.

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

Council of Science Editors:

-3562-6540. Learning and validating clinically meaningful phenotypes from electronic health data. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/69179

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


University of Texas – Austin

18. Khanna, Rajiv Ashu. New perspectives and applications for greedy algorithms in machine learning.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 Approximating probability densities is a core problem in Bayesian statistics, where the inference involves the computation of a posterior distribution. Variational Inference (VI) is a… (more)

Subjects/Keywords: Approximate inference; Submodularity

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APA (6th Edition):

Khanna, R. A. (2018). New perspectives and applications for greedy algorithms in machine learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/69183

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):

Khanna, Rajiv Ashu. “New perspectives and applications for greedy algorithms in machine learning.” 2018. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/69183.

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

MLA Handbook (7th Edition):

Khanna, Rajiv Ashu. “New perspectives and applications for greedy algorithms in machine learning.” 2018. Web. 25 Apr 2019.

Vancouver:

Khanna RA. New perspectives and applications for greedy algorithms in machine learning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/69183.

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

Council of Science Editors:

Khanna RA. New perspectives and applications for greedy algorithms in machine learning. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/69183

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


University of Texas – Austin

19. Zhang, Tong, active 2013. Generation planning using Screening Curve Method.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

 The Screening Curve Method (SCM) is an intuitive and fast model that estimates the least-cost generation mix for generation planning purposes. As an approximation method,… (more)

Subjects/Keywords: Generation planning; Screening Curve Method; Unit commitment; Economic dispatch; Ancillary services; Planned outage; Forced outage

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APA (6th Edition):

Zhang, Tong, a. 2. (2016). Generation planning using Screening Curve Method. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68262

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):

Zhang, Tong, active 2013. “Generation planning using Screening Curve Method.” 2016. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/68262.

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

MLA Handbook (7th Edition):

Zhang, Tong, active 2013. “Generation planning using Screening Curve Method.” 2016. Web. 25 Apr 2019.

Vancouver:

Zhang, Tong a2. Generation planning using Screening Curve Method. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/68262.

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

Council of Science Editors:

Zhang, Tong a2. Generation planning using Screening Curve Method. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/68262

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


University of Texas – Austin

20. Krumpelman, Chase Serhur. Overlapping clustering.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Analysis of large collections of data has become inescapable in many areas of scientific and commercial endeavor. As the size and dimensionality of these collections… (more)

Subjects/Keywords: Clustering algorithms

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APA (6th Edition):

Krumpelman, C. S. (2010). Overlapping clustering. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-2022

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):

Krumpelman, Chase Serhur. “Overlapping clustering.” 2010. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-2022.

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

MLA Handbook (7th Edition):

Krumpelman, Chase Serhur. “Overlapping clustering.” 2010. Web. 25 Apr 2019.

Vancouver:

Krumpelman CS. Overlapping clustering. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-2022.

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

Council of Science Editors:

Krumpelman CS. Overlapping clustering. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-2022

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


University of Texas – Austin

21. -3478-7289. Clinically interpretable models for healthcare data.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 The increasing availability of electronic health records (EHRs) has spurred the adoption of data-driven approaches to provide additional insights for diagnoses, prognoses, and cost-effective patient… (more)

Subjects/Keywords: Data mining; Healthcare data

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APA (6th Edition):

-3478-7289. (2015). Clinically interpretable models for healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33383

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

Chicago Manual of Style (16th Edition):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/33383.

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

MLA Handbook (7th Edition):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Web. 25 Apr 2019.

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

Vancouver:

-3478-7289. Clinically interpretable models for healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/33383.

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

Council of Science Editors:

-3478-7289. Clinically interpretable models for healthcare data. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33383

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


University of Texas – Austin

22. Lee, Sang Hyun, 1977-. On a class of distributed algorithms over networks and graphs.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 Distributed iterative algorithms are of great importance, as they are known to provide low-complexity and approximate solutions to what are otherwise high-dimensional intractable optimization problems.… (more)

Subjects/Keywords: Distributed algorithms; Graphical models; Belief propagation; Affinity propagation; Resource allocation; Genomic sequence analysis; Distributed iterative algorithms; Message-passing algorithms

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APA (6th Edition):

Lee, Sang Hyun, 1. (2011). On a class of distributed algorithms over networks and graphs. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3093

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):

Lee, Sang Hyun, 1977-. “On a class of distributed algorithms over networks and graphs.” 2011. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3093.

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

MLA Handbook (7th Edition):

Lee, Sang Hyun, 1977-. “On a class of distributed algorithms over networks and graphs.” 2011. Web. 25 Apr 2019.

Vancouver:

Lee, Sang Hyun 1. On a class of distributed algorithms over networks and graphs. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3093.

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

Council of Science Editors:

Lee, Sang Hyun 1. On a class of distributed algorithms over networks and graphs. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3093

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


University of Texas – Austin

23. Huynh, Tuyen Ngoc. Improving the accuracy and scalability of discriminative learning methods for Markov logic networks.

Degree: Computer Sciences, 2011, University of Texas – Austin

 Many real-world problems involve data that both have complex structures and uncertainty. Statistical relational learning (SRL) is an emerging area of research that addresses the… (more)

Subjects/Keywords: Markov logic networks; Statistical relational learning; Structured prediction; Logic networks; Artificial intelligence; Machine learning

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APA (6th Edition):

Huynh, T. N. (2011). Improving the accuracy and scalability of discriminative learning methods for Markov logic networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3436

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):

Huynh, Tuyen Ngoc. “Improving the accuracy and scalability of discriminative learning methods for Markov logic networks.” 2011. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3436.

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

MLA Handbook (7th Edition):

Huynh, Tuyen Ngoc. “Improving the accuracy and scalability of discriminative learning methods for Markov logic networks.” 2011. Web. 25 Apr 2019.

Vancouver:

Huynh TN. Improving the accuracy and scalability of discriminative learning methods for Markov logic networks. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3436.

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

Council of Science Editors:

Huynh TN. Improving the accuracy and scalability of discriminative learning methods for Markov logic networks. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3436

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


University of Texas – Austin

24. Gopinath, Ajay, 1980-. Feature modeling and tomographic reconstruction of electron microscopy images.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 This work introduces a combination of image processing and analysis methods that perform feature extraction, shape analysis and tomographic reconstruction of Electron Microscopy images. These… (more)

Subjects/Keywords: Electron microscopy; AIDS virus; GP 120 spike; Feature modeling; Tomographic reconstruction; Image processing; Inverse problems

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APA (6th Edition):

Gopinath, Ajay, 1. (2012). Feature modeling and tomographic reconstruction of electron microscopy images. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-4972

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):

Gopinath, Ajay, 1980-. “Feature modeling and tomographic reconstruction of electron microscopy images.” 2012. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-4972.

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

MLA Handbook (7th Edition):

Gopinath, Ajay, 1980-. “Feature modeling and tomographic reconstruction of electron microscopy images.” 2012. Web. 25 Apr 2019.

Vancouver:

Gopinath, Ajay 1. Feature modeling and tomographic reconstruction of electron microscopy images. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4972.

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

Council of Science Editors:

Gopinath, Ajay 1. Feature modeling and tomographic reconstruction of electron microscopy images. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4972

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


University of Texas – Austin

25. -7186-6405. Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications.

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

 Inference from high-dimensional noisy data, the task encountered in a wide range of applications including those in wireless communications and bioinformatics, is often computationally challenging.… (more)

Subjects/Keywords: Sparsity; Structures; Sphere decoding; Haplotype; Quasispecies; Clustering; Matrix factorization; Bioinformatics

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APA (6th Edition):

-7186-6405. (2017). Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61549

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

Chicago Manual of Style (16th Edition):

-7186-6405. “Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications.” 2017. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/61549.

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

MLA Handbook (7th Edition):

-7186-6405. “Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications.” 2017. Web. 25 Apr 2019.

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

Vancouver:

-7186-6405. Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/61549.

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

Council of Science Editors:

-7186-6405. Algorithms for sparse and structurally constrained discrete optimization problems in bioinformatics and communications. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61549

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


University of Texas – Austin

26. https://orcid.org/0000-0002-8791-7828. Listwise frameworks for ranking and rank aggregation.

Degree: Computer Sciences, 2018, University of Texas – Austin

 The goal in Learning to Rank (LETOR) is to learn to order a novel set of items, given training data comprising sets of items and… (more)

Subjects/Keywords: Machine learning; Ranking; Learning to rank; Rank aggregation; Listwise methods; Tracking

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APA (6th Edition):

https://orcid.org/0000-0002-8791-7828. (2018). Listwise frameworks for ranking and rank aggregation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63694

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

Chicago Manual of Style (16th Edition):

https://orcid.org/0000-0002-8791-7828. “Listwise frameworks for ranking and rank aggregation.” 2018. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/63694.

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

MLA Handbook (7th Edition):

https://orcid.org/0000-0002-8791-7828. “Listwise frameworks for ranking and rank aggregation.” 2018. Web. 25 Apr 2019.

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

Vancouver:

https://orcid.org/0000-0002-8791-7828. Listwise frameworks for ranking and rank aggregation. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/63694.

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

Council of Science Editors:

https://orcid.org/0000-0002-8791-7828. Listwise frameworks for ranking and rank aggregation. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63694

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


University of Texas – Austin

27. -3113-0409. Outcome prediction and structure discovery in healthcare data.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

 Growing use of electronic medical records, advances in data mining and machine learning, and the continually increasing cost of healthcare in the United States drive… (more)

Subjects/Keywords: Healthcare analytics; Mortality prediction; Optimizable risk score; Affinity propagation; Semi-supervised clustering; Noisy pairwise constraints; Evolutionary clustering; Temporal data; Medication adherence

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APA (6th Edition):

-3113-0409. (2016). Outcome prediction and structure discovery in healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43726

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

Chicago Manual of Style (16th Edition):

-3113-0409. “Outcome prediction and structure discovery in healthcare data.” 2016. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/43726.

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

MLA Handbook (7th Edition):

-3113-0409. “Outcome prediction and structure discovery in healthcare data.” 2016. Web. 25 Apr 2019.

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

Vancouver:

-3113-0409. Outcome prediction and structure discovery in healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/43726.

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

Council of Science Editors:

-3113-0409. Outcome prediction and structure discovery in healthcare data. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43726

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


University of Texas – Austin

28. Gunasekar, Suriya. Mining structured matrices in high dimensions.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

 Structured matrices refer to matrix valued data that are embedded in an inherent lower dimensional manifold with smaller degrees of freedom compared to the ambient… (more)

Subjects/Keywords: Matrix completion; High dimensional estimation; EHRs; Letor; Matrix estimation; Sample complexity

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

APA (6th Edition):

Gunasekar, S. (2016). Mining structured matrices in high dimensions. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43772

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):

Gunasekar, Suriya. “Mining structured matrices in high dimensions.” 2016. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/43772.

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

MLA Handbook (7th Edition):

Gunasekar, Suriya. “Mining structured matrices in high dimensions.” 2016. Web. 25 Apr 2019.

Vancouver:

Gunasekar S. Mining structured matrices in high dimensions. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/43772.

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

Council of Science Editors:

Gunasekar S. Mining structured matrices in high dimensions. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43772

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

29. Bayzid, Md. Shamsuzzoha. Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions.

Degree: Computer Sciences, 2016, University of Texas – Austin

 Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. With the rapid growth rate of newly sequenced… (more)

Subjects/Keywords: Phylogenetic tree; Species tree; Gene tree; Incomplete lineage sorting (ILS); Deep coalescence; Gene duplication and loss; Multi-species coalescent model; Phylogenomic analyses; Gene tree discordance

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

APA (6th Edition):

Bayzid, M. S. (2016). Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46404

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):

Bayzid, Md Shamsuzzoha. “Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions.” 2016. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/46404.

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

MLA Handbook (7th Edition):

Bayzid, Md Shamsuzzoha. “Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions.” 2016. Web. 25 Apr 2019.

Vancouver:

Bayzid MS. Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/46404.

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

Council of Science Editors:

Bayzid MS. Estimating species trees from gene trees despite gene tree incongruence under realistic model conditions. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46404

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


University of Texas – Austin

30. Verma, Nishant. Biomarker for tracking progression of Alzheimer's disease in clinical trials.

Degree: Biomedical Engineering, 2015, University of Texas – Austin

 Currently, there are no treatments available for mitigating the neurological effects of Alzheimer's disease. All clinical trials of disease-modifying treatments, which showed promise in animal… (more)

Subjects/Keywords: Alzheimer's disease; Clinical trials; Alzheimer's Disease Assessment Scale-Cognitive subscale; Item response theory; ADAS-Cog; Cognitive impairment; MCI; Clinical trial efficiency; MCI stage; Prodromal stage; Cerebral atrophy; MR volumes; Automatic tissue segmentation; Biomarkers; Alzheimer’s biomarkers; ADAS-Cog scoring methodology

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

APA (6th Edition):

Verma, N. (2015). Biomarker for tracking progression of Alzheimer's disease in clinical trials. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46741

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):

Verma, Nishant. “Biomarker for tracking progression of Alzheimer's disease in clinical trials.” 2015. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/46741.

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

MLA Handbook (7th Edition):

Verma, Nishant. “Biomarker for tracking progression of Alzheimer's disease in clinical trials.” 2015. Web. 25 Apr 2019.

Vancouver:

Verma N. Biomarker for tracking progression of Alzheimer's disease in clinical trials. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/46741.

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

Council of Science Editors:

Verma N. Biomarker for tracking progression of Alzheimer's disease in clinical trials. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/46741

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

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