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You searched for +publisher:"University of Texas – Austin" +contributor:("Mooney, Raymond"). Showing records 1 – 30 of 58 total matches.

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University of Texas – Austin

1. Reisinger, Joseph Simon. Latent variable models of distributional lexical semantics.

Degree: Computer Sciences, 2012, University of Texas – Austin

 In order to respond to increasing demand for natural language interfaces – and provide meaningful insight into user query intent – fast, scalable lexical semantic models with… (more)

Subjects/Keywords: Lexical semantics; Natural language processing; Machine learning

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

APA (6th Edition):

Reisinger, J. S. (2012). Latent variable models of distributional lexical semantics. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26889

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):

Reisinger, Joseph Simon. “Latent variable models of distributional lexical semantics.” 2012. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/26889.

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

MLA Handbook (7th Edition):

Reisinger, Joseph Simon. “Latent variable models of distributional lexical semantics.” 2012. Web. 27 May 2019.

Vancouver:

Reisinger JS. Latent variable models of distributional lexical semantics. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/26889.

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

Council of Science Editors:

Reisinger JS. Latent variable models of distributional lexical semantics. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/26889

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


University of Texas – Austin

2. Mihalkova, Lilyana Simeonova. Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation.

Degree: Computer Sciences, 2009, University of Texas – Austin

 Traditionally, machine learning algorithms assume that training data is provided as a set of independent instances, each of which can be described as a feature… (more)

Subjects/Keywords: Markov logic networks; Web query disambiguation; Statistical Relational Learning; Artificial intelligence; Machine learning; Multi-relational data; First-order logic; Probability distribution; Structure learning; Transfer learning; Algorithms

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

APA (6th Edition):

Mihalkova, L. S. (2009). Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/10574

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):

Mihalkova, Lilyana Simeonova. “Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation.” 2009. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/10574.

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

MLA Handbook (7th Edition):

Mihalkova, Lilyana Simeonova. “Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation.” 2009. Web. 27 May 2019.

Vancouver:

Mihalkova LS. Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/10574.

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

Council of Science Editors:

Mihalkova LS. Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/10574

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


University of Texas – Austin

3. Ge, Ruifang. Learning for semantic parsing using statistical syntactic parsing techniques.

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

 Natural language understanding is a sub-field of natural language processing, which builds automated systems to understand natural language. It is such an ambitious task that… (more)

Subjects/Keywords: Semantic parsing; Statistical syntactic parsing

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APA (6th Edition):

Ge, R. (2010). Learning for semantic parsing using statistical syntactic parsing techniques. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26599

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):

Ge, Ruifang. “Learning for semantic parsing using statistical syntactic parsing techniques.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/26599.

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

MLA Handbook (7th Edition):

Ge, Ruifang. “Learning for semantic parsing using statistical syntactic parsing techniques.” 2010. Web. 27 May 2019.

Vancouver:

Ge R. Learning for semantic parsing using statistical syntactic parsing techniques. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/26599.

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

Council of Science Editors:

Ge R. Learning for semantic parsing using statistical syntactic parsing techniques. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/26599

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


University of Texas – Austin

4. Ramanujam, Srivatsan. Factorial Hidden Markov Models for full and weakly supervised supertagging.

Degree: Computer Sciences, 2009, University of Texas – Austin

 For many sequence prediction tasks in Natural Language Processing, modeling dependencies between individual predictions can be used to improve prediction accuracy of the sequence as… (more)

Subjects/Keywords: Hidden Markov Models; Bayesian Models; Categorial Grammar; Supertagging; Joint Inference

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APA (6th Edition):

Ramanujam, S. (2009). Factorial Hidden Markov Models for full and weakly supervised supertagging. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-08-350

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):

Ramanujam, Srivatsan. “Factorial Hidden Markov Models for full and weakly supervised supertagging.” 2009. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2009-08-350.

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

MLA Handbook (7th Edition):

Ramanujam, Srivatsan. “Factorial Hidden Markov Models for full and weakly supervised supertagging.” 2009. Web. 27 May 2019.

Vancouver:

Ramanujam S. Factorial Hidden Markov Models for full and weakly supervised supertagging. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-350.

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

Council of Science Editors:

Ramanujam S. Factorial Hidden Markov Models for full and weakly supervised supertagging. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-350

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


University of Texas – Austin

5. Gupta, Sonal. Activity retrieval in closed captioned videos.

Degree: Computer Sciences, 2009, University of Texas – Austin

 Recognizing activities in real-world videos is a difficult problem exacerbated by background clutter, changes in camera angle & zoom, occlusion and rapid camera movements. Large… (more)

Subjects/Keywords: Activity Recognition; Action Recognition; Video Retrieval; Machine Learning; Computer Vision; Multimedia; Closed Captions

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

APA (6th Edition):

Gupta, S. (2009). Activity retrieval in closed captioned videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-08-305

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):

Gupta, Sonal. “Activity retrieval in closed captioned videos.” 2009. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2009-08-305.

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

MLA Handbook (7th Edition):

Gupta, Sonal. “Activity retrieval in closed captioned videos.” 2009. Web. 27 May 2019.

Vancouver:

Gupta S. Activity retrieval in closed captioned videos. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-305.

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

Council of Science Editors:

Gupta S. Activity retrieval in closed captioned videos. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-305

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


University of Texas – Austin

6. Chaurasia, Shobhit. Dialog for natural language to code.

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

 Generating computer code from natural language descriptions has been a long-standing problem in computational linguistics. Prior work in this domain has restricted itself to generating… (more)

Subjects/Keywords: Dialog; Interactive systems; Neural network; Deep learning; Semantic parsing; Computer code; Software engineering

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

APA (6th Edition):

Chaurasia, S. (2017). Dialog for natural language to code. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62886

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):

Chaurasia, Shobhit. “Dialog for natural language to code.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/62886.

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

MLA Handbook (7th Edition):

Chaurasia, Shobhit. “Dialog for natural language to code.” 2017. Web. 27 May 2019.

Vancouver:

Chaurasia S. Dialog for natural language to code. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/62886.

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

Council of Science Editors:

Chaurasia S. Dialog for natural language to code. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62886

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


University of Texas – Austin

7. Yaghmazadeh, Navid. Automated synthesis of data extraction and transformation programs.

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

 Due to the abundance of data in today’s data-rich world, end-users increasingly need to perform various data extraction and transformation tasks. While many of these… (more)

Subjects/Keywords: Program synthesis; Programming-by-examples; Programming-by-natural-language; Databases

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

APA (6th Edition):

Yaghmazadeh, N. (2017). Automated synthesis of data extraction and transformation programs. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68138

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):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/68138.

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

MLA Handbook (7th Edition):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Web. 27 May 2019.

Vancouver:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/68138.

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

Council of Science Editors:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/68138

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


University of Texas – Austin

8. Roller, Stephen Creig. Identifying lexical relationships and entailments with distributional semantics.

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

 Many modern efforts in Natural Language Understanding depend on rich and powerful semantic representations of words. Systems for sophisticated logical and textual reasoning often depend… (more)

Subjects/Keywords: Natural language processing; Lexical semantics; Lexical relationships; Hypernymy; Distributional semantics

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

APA (6th Edition):

Roller, S. C. (2017). Identifying lexical relationships and entailments with distributional semantics. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61528

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):

Roller, Stephen Creig. “Identifying lexical relationships and entailments with distributional semantics.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/61528.

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

MLA Handbook (7th Edition):

Roller, Stephen Creig. “Identifying lexical relationships and entailments with distributional semantics.” 2017. Web. 27 May 2019.

Vancouver:

Roller SC. Identifying lexical relationships and entailments with distributional semantics. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/61528.

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

Council of Science Editors:

Roller SC. Identifying lexical relationships and entailments with distributional semantics. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61528

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


University of Texas – Austin

9. -9199-0633. Continually improving grounded natural language understanding through human-robot dialog.

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

 As robots become ubiquitous in homes and workplaces such as hospitals and factories, they must be able to communicate with humans. Several kinds of knowledge… (more)

Subjects/Keywords: Natural language processing; Human-robot dialog

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APA (6th Edition):

-9199-0633. (2018). Continually improving grounded natural language understanding through human-robot dialog. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68120

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):

-9199-0633. “Continually improving grounded natural language understanding through human-robot dialog.” 2018. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/68120.

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):

-9199-0633. “Continually improving grounded natural language understanding through human-robot dialog.” 2018. Web. 27 May 2019.

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

Vancouver:

-9199-0633. Continually improving grounded natural language understanding through human-robot dialog. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/68120.

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:

-9199-0633. Continually improving grounded natural language understanding through human-robot dialog. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68120

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

10. Feng, Yu, Ph. D. Program synthesis using statistical models and logical reasoning.

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

 Complex APIs in new frameworks (Spark, R, TensorFlow, etc) have imposed steep learning curves on everyone, especially for people with limited programming backgrounds. For instance,… (more)

Subjects/Keywords: Program synthesis; Logical reasoning

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APA (6th Edition):

Feng, Yu, P. D. (2018). Program synthesis using statistical models and logical reasoning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68452

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):

Feng, Yu, Ph D. “Program synthesis using statistical models and logical reasoning.” 2018. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/68452.

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

MLA Handbook (7th Edition):

Feng, Yu, Ph D. “Program synthesis using statistical models and logical reasoning.” 2018. Web. 27 May 2019.

Vancouver:

Feng, Yu PD. Program synthesis using statistical models and logical reasoning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/68452.

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

Council of Science Editors:

Feng, Yu PD. Program synthesis using statistical models and logical reasoning. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68452

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


University of Texas – Austin

11. Kuhlmann, Gregory John. Automated domain analysis and transfer learning in general game playing.

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

 Creating programs that can play games such as chess, checkers, and backgammon, at a high level has long been a challenge and benchmark for AI.… (more)

Subjects/Keywords: Games; Machine learning; Knowledge transfer; Reinforcement learning; General game playing; Computer games; Artificial Intelligence; AI

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APA (6th Edition):

Kuhlmann, G. J. (2010). Automated domain analysis and transfer learning in general game playing. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1975

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):

Kuhlmann, Gregory John. “Automated domain analysis and transfer learning in general game playing.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1975.

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

MLA Handbook (7th Edition):

Kuhlmann, Gregory John. “Automated domain analysis and transfer learning in general game playing.” 2010. Web. 27 May 2019.

Vancouver:

Kuhlmann GJ. Automated domain analysis and transfer learning in general game playing. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1975.

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

Council of Science Editors:

Kuhlmann GJ. Automated domain analysis and transfer learning in general game playing. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1975

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


University of Texas – Austin

12. 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 May 27, 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. 27 May 2019.

Vancouver:

Krumpelman CS. Overlapping clustering. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. 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

13. -5892-1089. Temporal modeling of crowd work quality for quality assurance in crowdsourcing.

Degree: Information, 2015, University of Texas – Austin

 While crowdsourcing offers potential traction on data collection at scale, it also poses new and significant quality concerns. Beyond the obvious issue of any new… (more)

Subjects/Keywords: Crowdsourcing; Quality assurance; Time-series; Prediction; Measurement

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APA (6th Edition):

-5892-1089. (2015). Temporal modeling of crowd work quality for quality assurance in crowdsourcing. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33261

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):

-5892-1089. “Temporal modeling of crowd work quality for quality assurance in crowdsourcing.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/33261.

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):

-5892-1089. “Temporal modeling of crowd work quality for quality assurance in crowdsourcing.” 2015. Web. 27 May 2019.

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

Vancouver:

-5892-1089. Temporal modeling of crowd work quality for quality assurance in crowdsourcing. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/33261.

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:

-5892-1089. Temporal modeling of crowd work quality for quality assurance in crowdsourcing. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33261

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

14. Whang, Joyce Jiyoung. Overlapping community detection in massive social networks.

Degree: Computer Sciences, 2015, University of Texas – Austin

 Massive social networks have become increasingly popular in recent years. Community detection is one of the most important techniques for the analysis of such complex… (more)

Subjects/Keywords: Community detection; Clustering; Social networks; Overlapping communities; Overlapping clusters; Non-exhaustive clustering; Seed expansion; K-means; Semidefinite programming; Co-clustering; PageRank; Data-driven algorithm; Scalable computing

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APA (6th Edition):

Whang, J. J. (2015). Overlapping community detection in massive social networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33272

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):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/33272.

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

MLA Handbook (7th Edition):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Web. 27 May 2019.

Vancouver:

Whang JJ. Overlapping community detection in massive social networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/33272.

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

Council of Science Editors:

Whang JJ. Overlapping community detection in massive social networks. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33272

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


University of Texas – Austin

15. Chen, Chao-Yeh. Learning human activities and poses with interconnected data sources.

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

 Understanding human actions and poses in images or videos is a challenging problem in computer vision. There are different topics related to this problem such… (more)

Subjects/Keywords: Activity recognition; Activity detection

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

APA (6th Edition):

Chen, C. (2016). Learning human activities and poses with interconnected data sources. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/40260

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

Chicago Manual of Style (16th Edition):

Chen, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/40260.

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

MLA Handbook (7th Edition):

Chen, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Web. 27 May 2019.

Vancouver:

Chen C. Learning human activities and poses with interconnected data sources. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/40260.

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

Council of Science Editors:

Chen C. Learning human activities and poses with interconnected data sources. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/40260

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


University of Texas – Austin

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

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 May 27, 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. 27 May 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 May 27]. 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

17. Jong, Nicholas K. Structured exploration for reinforcement learning.

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

 Reinforcement Learning (RL) offers a promising approach towards achieving the dream of autonomous agents that can behave intelligently in the real world. Instead of requiring… (more)

Subjects/Keywords: Reinforcement learning; Machine learning

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APA (6th Edition):

Jong, N. K. (2010). Structured exploration for reinforcement learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-12-2448

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):

Jong, Nicholas K. “Structured exploration for reinforcement learning.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2010-12-2448.

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

MLA Handbook (7th Edition):

Jong, Nicholas K. “Structured exploration for reinforcement learning.” 2010. Web. 27 May 2019.

Vancouver:

Jong NK. Structured exploration for reinforcement learning. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2448.

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

Council of Science Editors:

Jong NK. Structured exploration for reinforcement learning. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2448

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


University of Texas – Austin

18. 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 May 27, 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. 27 May 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 May 27]. 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

19. Si, Si, Ph.D. Large-scale non-linear prediction with applications.

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

 With an immense growth in data, there is a great need for training and testing machine learning models on very large data sets. Several standard… (more)

Subjects/Keywords: Kernel methods; Classification; Decision trees

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

APA (6th Edition):

Si, Si, P. D. (2016). Large-scale non-linear prediction with applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43583

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):

Si, Si, Ph D. “Large-scale non-linear prediction with applications.” 2016. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/43583.

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

MLA Handbook (7th Edition):

Si, Si, Ph D. “Large-scale non-linear prediction with applications.” 2016. Web. 27 May 2019.

Vancouver:

Si, Si PD. Large-scale non-linear prediction with applications. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/43583.

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

Council of Science Editors:

Si, Si PD. Large-scale non-linear prediction with applications. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43583

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


University of Texas – Austin

20. Garrette, Daniel Hunter. Inducing grammars from linguistic universals and realistic amounts of supervision.

Degree: Computer Sciences, 2015, University of Texas – Austin

 The best performing NLP models to date are learned from large volumes of manually-annotated data. For tasks like part-of-speech tagging and grammatical parsing, high performance… (more)

Subjects/Keywords: Computer science; Artificial intelligence; Natural language processing; Machine learning; Bayesian statistics; Grammar induction; Parsing; Computational linguistics

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APA (6th Edition):

Garrette, D. H. (2015). Inducing grammars from linguistic universals and realistic amounts of supervision. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/44478

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):

Garrette, Daniel Hunter. “Inducing grammars from linguistic universals and realistic amounts of supervision.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/44478.

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

MLA Handbook (7th Edition):

Garrette, Daniel Hunter. “Inducing grammars from linguistic universals and realistic amounts of supervision.” 2015. Web. 27 May 2019.

Vancouver:

Garrette DH. Inducing grammars from linguistic universals and realistic amounts of supervision. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/44478.

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

Council of Science Editors:

Garrette DH. Inducing grammars from linguistic universals and realistic amounts of supervision. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/44478

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


University of Texas – Austin

21. -4493-3358. Appropriate, accessible and appealing probabilistic graphical models.

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

 Appropriate - Many multivariate probabilistic models either use independent distributions or dependent Gaussian distributions. Yet, many real-world datasets contain count-valued or non-negative skewed data, e.g.… (more)

Subjects/Keywords: Graphical models; Topic models; Poisson; Count data; Visualization; Human computer interaction

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APA (6th Edition):

-4493-3358. (2017). Appropriate, accessible and appealing probabilistic graphical models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62986

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):

-4493-3358. “Appropriate, accessible and appealing probabilistic graphical models.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/62986.

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):

-4493-3358. “Appropriate, accessible and appealing probabilistic graphical models.” 2017. Web. 27 May 2019.

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

Vancouver:

-4493-3358. Appropriate, accessible and appealing probabilistic graphical models. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/62986.

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:

-4493-3358. Appropriate, accessible and appealing probabilistic graphical models. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62986

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. -3729-8456. Natural-language video description with deep recurrent neural networks.

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

 For most people, watching a brief video and describing what happened (in words) is an easy task. For machines, extracting meaning from video pixels and… (more)

Subjects/Keywords: Video; Captioning; Description; LSTM; RNN; Recurrent; Neural networks; Image captioning; Video captioning; Language and vision

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

APA (6th Edition):

-3729-8456. (2017). Natural-language video description with deep recurrent neural networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62987

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):

-3729-8456. “Natural-language video description with deep recurrent neural networks.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/62987.

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):

-3729-8456. “Natural-language video description with deep recurrent neural networks.” 2017. Web. 27 May 2019.

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

Vancouver:

-3729-8456. Natural-language video description with deep recurrent neural networks. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/62987.

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:

-3729-8456. Natural-language video description with deep recurrent neural networks. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62987

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

23. Jain, Suyog Dutt. Human machine collaboration for foreground segmentation in images and videos.

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

 Foreground segmentation is defined as the problem of generating pixel level foreground masks for all the objects in a given image or video. Accurate foreground… (more)

Subjects/Keywords: Computer vision; Crowdsourcing; Human machine collaboration; Image and video segmentation; Image segmentation; Video segmentation; Foreground segmentation; Object segmentation

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

APA (6th Edition):

Jain, S. D. (2018). Human machine collaboration for foreground segmentation in images and videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63453

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):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/63453.

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

MLA Handbook (7th Edition):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Web. 27 May 2019.

Vancouver:

Jain SD. Human machine collaboration for foreground segmentation in images and videos. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/63453.

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

Council of Science Editors:

Jain SD. Human machine collaboration for foreground segmentation in images and videos. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63453

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


University of Texas – Austin

24. -7062-2970. Advances in statistical script learning.

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

 When humans encode information into natural language, they do so with the clear assumption that the reader will be able to seamlessly make inferences based… (more)

Subjects/Keywords: Natural language processing; Machine learning

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

APA (6th Edition):

-7062-2970. (2017). Advances in statistical script learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63480

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):

-7062-2970. “Advances in statistical script learning.” 2017. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/63480.

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):

-7062-2970. “Advances in statistical script learning.” 2017. Web. 27 May 2019.

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

Vancouver:

-7062-2970. Advances in statistical script learning. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/63480.

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:

-7062-2970. Advances in statistical script learning. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63480

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

25. -3023-4337. Knowledge transfer using latent variable models.

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

 In several applications, scarcity of labeled data is a challenging problem that hinders the predictive capabilities of machine learning algorithms. Additionally, the distribution of the… (more)

Subjects/Keywords: Transfer learning; Multitask learning; Gamma process; Poisson factorization; Supervised topic model

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

APA (6th Edition):

-3023-4337. (2015). Knowledge transfer using latent variable models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31414

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):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/31414.

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):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Web. 27 May 2019.

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

Vancouver:

-3023-4337. Knowledge transfer using latent variable models. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/31414.

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:

-3023-4337. Knowledge transfer using latent variable models. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31414

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

26. Urieli, Daniel. Autonomous trading in modern electricity markets.

Degree: Computer Sciences, 2015, University of Texas – Austin

 The smart grid is an electricity grid augmented with digital technologies that automate the management of electricity delivery. The smart grid is envisioned to be… (more)

Subjects/Keywords: Autonomous electricity trading; Smart grid; Electricity markets; Power markets; Planning; Lookahead planning; Monte-Carlo planning; Learning agents; Embedded machine learning; Machine learning; Reinforcement learning

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APA (6th Edition):

Urieli, D. (2015). Autonomous trading in modern electricity markets. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39597

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):

Urieli, Daniel. “Autonomous trading in modern electricity markets.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/39597.

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

MLA Handbook (7th Edition):

Urieli, Daniel. “Autonomous trading in modern electricity markets.” 2015. Web. 27 May 2019.

Vancouver:

Urieli D. Autonomous trading in modern electricity markets. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/39597.

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

Council of Science Editors:

Urieli D. Autonomous trading in modern electricity markets. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/39597

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

27. Beltagy, Islam Kamel Ahmed. Natural language semantics using probabilistic logic.

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

 With better natural language semantic representations, computers can do more applications more efficiently as a result of better understanding of natural text. However, no single… (more)

Subjects/Keywords: NLP; Machine learning; Probabilistic logic; MLNs; PSL; Markov Logic Network; QA; RTE; STS

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

APA (6th Edition):

Beltagy, I. K. A. (2016). Natural language semantics using probabilistic logic. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46617

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):

Beltagy, Islam Kamel Ahmed. “Natural language semantics using probabilistic logic.” 2016. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/46617.

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

MLA Handbook (7th Edition):

Beltagy, Islam Kamel Ahmed. “Natural language semantics using probabilistic logic.” 2016. Web. 27 May 2019.

Vancouver:

Beltagy IKA. Natural language semantics using probabilistic logic. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/46617.

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

Council of Science Editors:

Beltagy IKA. Natural language semantics using probabilistic logic. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46617

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


University of Texas – Austin

28. Mugan, Jonathan William. Autonomous qualitative learning of distinctions and actions in a developing agent.

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

 How can an agent bootstrap up from a pixel-level representation to autonomously learn high-level states and actions using only domain general knowledge? This thesis attacks… (more)

Subjects/Keywords: Artificial intelligence; Robotics; Machine learning; Reinforcement learning; Discretization; Qualitative learning

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APA (6th Edition):

Mugan, J. W. (2010). Autonomous qualitative learning of distinctions and actions in a developing agent. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1726

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):

Mugan, Jonathan William. “Autonomous qualitative learning of distinctions and actions in a developing agent.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1726.

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

MLA Handbook (7th Edition):

Mugan, Jonathan William. “Autonomous qualitative learning of distinctions and actions in a developing agent.” 2010. Web. 27 May 2019.

Vancouver:

Mugan JW. Autonomous qualitative learning of distinctions and actions in a developing agent. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1726.

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

Council of Science Editors:

Mugan JW. Autonomous qualitative learning of distinctions and actions in a developing agent. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1726

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


University of Texas – Austin

29. Cho, Tae Won, 1978-. Enabling information-centric networking : architecture, protocols, and applications.

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

 As the Internet is becoming information-centric, network services increasingly demand scalable and efficient communication of information between a multitude of information producers and large groups… (more)

Subjects/Keywords: Information-centric networking; Network protocols; Social networks; Multicast; Networks; Proximity measures; Link prediction

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

APA (6th Edition):

Cho, Tae Won, 1. (2010). Enabling information-centric networking : architecture, protocols, and applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1765

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):

Cho, Tae Won, 1978-. “Enabling information-centric networking : architecture, protocols, and applications.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1765.

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

MLA Handbook (7th Edition):

Cho, Tae Won, 1978-. “Enabling information-centric networking : architecture, protocols, and applications.” 2010. Web. 27 May 2019.

Vancouver:

Cho, Tae Won 1. Enabling information-centric networking : architecture, protocols, and applications. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1765.

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

Council of Science Editors:

Cho, Tae Won 1. Enabling information-centric networking : architecture, protocols, and applications. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1765

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


University of Texas – Austin

30. Ramakrishnan, Smriti Rajan. A systems approach to computational protein identification.

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

 Proteomics is the science of understanding the dynamic protein content of an organism's cells (its proteome), which is one of the largest current challenges in… (more)

Subjects/Keywords: Computational biology; Bioinformatics; Integrative statistical data analysis; Computational proteomics; Systems biology; Database indexing

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

APA (6th Edition):

Ramakrishnan, S. R. (2010). A systems approach to computational protein identification. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-05-1036

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):

Ramakrishnan, Smriti Rajan. “A systems approach to computational protein identification.” 2010. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/ETD-UT-2010-05-1036.

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

MLA Handbook (7th Edition):

Ramakrishnan, Smriti Rajan. “A systems approach to computational protein identification.” 2010. Web. 27 May 2019.

Vancouver:

Ramakrishnan SR. A systems approach to computational protein identification. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1036.

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

Council of Science Editors:

Ramakrishnan SR. A systems approach to computational protein identification. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1036

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

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