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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. -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 June 24, 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. 24 Jun 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 Jun 24]. 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

2. 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 (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 June 24, 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. 24 Jun 2019.

Vancouver:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Jun 24]. 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

3. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Feng, Yu PD. Program synthesis using statistical models and logical reasoning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 24]. 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

4. Bilenko, Mikhail Yuryevich. Learnable similarity functions and their application to record linkage and clustering.

Degree: Computer Sciences, 2006, University of Texas – Austin

 Many machine learning and data mining tasks depend on functions that estimate similarity between instances. Similarity computations are particularly important in clustering and information integration… (more)

Subjects/Keywords: Cluster analysis – Data processing; Pattern recognition systems; Machine learning

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APA (6th Edition):

Bilenko, M. Y. (2006). Learnable similarity functions and their application to record linkage and clustering. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/2681

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):

Bilenko, Mikhail Yuryevich. “Learnable similarity functions and their application to record linkage and clustering.” 2006. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/2681.

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

MLA Handbook (7th Edition):

Bilenko, Mikhail Yuryevich. “Learnable similarity functions and their application to record linkage and clustering.” 2006. Web. 24 Jun 2019.

Vancouver:

Bilenko MY. Learnable similarity functions and their application to record linkage and clustering. [Internet] [Thesis]. University of Texas – Austin; 2006. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/2681.

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

Council of Science Editors:

Bilenko MY. Learnable similarity functions and their application to record linkage and clustering. [Thesis]. University of Texas – Austin; 2006. Available from: http://hdl.handle.net/2152/2681

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


University of Texas – Austin

5. Bunescu, Razvan Constantin, 1975-. Learning for information extraction: from named entity recognition and disambiguation to relation extraction.

Degree: Computer Sciences, 2007, University of Texas – Austin

 Information Extraction, the task of locating textual mentions of specific types of entities and their relationships, aims at representing the information contained in text documents… (more)

Subjects/Keywords: Natural language processing (Computer science); Information storage and retrieval systems

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APA (6th Edition):

Bunescu, Razvan Constantin, 1. (2007). Learning for information extraction: from named entity recognition and disambiguation to relation extraction. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3200

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):

Bunescu, Razvan Constantin, 1975-. “Learning for information extraction: from named entity recognition and disambiguation to relation extraction.” 2007. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/3200.

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

MLA Handbook (7th Edition):

Bunescu, Razvan Constantin, 1975-. “Learning for information extraction: from named entity recognition and disambiguation to relation extraction.” 2007. Web. 24 Jun 2019.

Vancouver:

Bunescu, Razvan Constantin 1. Learning for information extraction: from named entity recognition and disambiguation to relation extraction. [Internet] [Thesis]. University of Texas – Austin; 2007. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/3200.

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

Council of Science Editors:

Bunescu, Razvan Constantin 1. Learning for information extraction: from named entity recognition and disambiguation to relation extraction. [Thesis]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3200

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


University of Texas – Austin

6. Kate, Rohit Jaivant, 1978-. Learning for semantic parsing with kernels under various forms of supervision.

Degree: Computer Sciences, 2007, University of Texas – Austin

 Semantic parsing involves deep semantic analysis that maps natural language sentences to their formal executable meaning representations. This is a challenging problem and is critical… (more)

Subjects/Keywords: Parsing (Computer grammar); Machine learning; Natural language processing (Computer science)

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APA (6th Edition):

Kate, Rohit Jaivant, 1. (2007). Learning for semantic parsing with kernels under various forms of supervision. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3272

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):

Kate, Rohit Jaivant, 1978-. “Learning for semantic parsing with kernels under various forms of supervision.” 2007. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/3272.

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

MLA Handbook (7th Edition):

Kate, Rohit Jaivant, 1978-. “Learning for semantic parsing with kernels under various forms of supervision.” 2007. Web. 24 Jun 2019.

Vancouver:

Kate, Rohit Jaivant 1. Learning for semantic parsing with kernels under various forms of supervision. [Internet] [Thesis]. University of Texas – Austin; 2007. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/3272.

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

Council of Science Editors:

Kate, Rohit Jaivant 1. Learning for semantic parsing with kernels under various forms of supervision. [Thesis]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3272

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


University of Texas – Austin

7. Wong, Yuk Wah, 1979-. Learning for semantic parsing and natural language generation using statistical machine translation techniques.

Degree: Computer Sciences, 2007, University of Texas – Austin

 One of the main goals of natural language processing (NLP) is to build au- tomated systems that can understand and generate human lanugages. This goal… (more)

Subjects/Keywords: Natural language processing (Computer science); Parsing (Computer grammar)

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APA (6th Edition):

Wong, Yuk Wah, 1. (2007). Learning for semantic parsing and natural language generation using statistical machine translation techniques. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3351

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):

Wong, Yuk Wah, 1979-. “Learning for semantic parsing and natural language generation using statistical machine translation techniques.” 2007. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/3351.

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

MLA Handbook (7th Edition):

Wong, Yuk Wah, 1979-. “Learning for semantic parsing and natural language generation using statistical machine translation techniques.” 2007. Web. 24 Jun 2019.

Vancouver:

Wong, Yuk Wah 1. Learning for semantic parsing and natural language generation using statistical machine translation techniques. [Internet] [Thesis]. University of Texas – Austin; 2007. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/3351.

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

Council of Science Editors:

Wong, Yuk Wah 1. Learning for semantic parsing and natural language generation using statistical machine translation techniques. [Thesis]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3351

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


University of Texas – Austin

8. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Ramanujam S. Factorial Hidden Markov Models for full and weakly supervised supertagging. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Jun 24]. 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

9. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Gupta S. Activity retrieval in closed captioned videos. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Jun 24]. 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

10. 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 (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 June 24, 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. 24 Jun 2019.

Vancouver:

Ramakrishnan SR. A systems approach to computational protein identification. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jun 24]. 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


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 June 24, 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. 24 Jun 2019.

Vancouver:

Kuhlmann GJ. Automated domain analysis and transfer learning in general game playing. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jun 24]. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Krumpelman CS. Overlapping clustering. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jun 24]. 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. Basu, Sugato. Semi-supervised clustering: probabilistic models, algorithms and experiments.

Degree: Computer Sciences, 2005, University of Texas – Austin

 Clustering is one of the most common data mining tasks, used frequently for data categorization and analysis in both industry and academia. The focus of… (more)

Subjects/Keywords: Cluster analysis; Computer algorithms

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APA (6th Edition):

Basu, S. (2005). Semi-supervised clustering: probabilistic models, algorithms and experiments. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/1820

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):

Basu, Sugato. “Semi-supervised clustering: probabilistic models, algorithms and experiments.” 2005. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/1820.

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

MLA Handbook (7th Edition):

Basu, Sugato. “Semi-supervised clustering: probabilistic models, algorithms and experiments.” 2005. Web. 24 Jun 2019.

Vancouver:

Basu S. Semi-supervised clustering: probabilistic models, algorithms and experiments. [Internet] [Thesis]. University of Texas – Austin; 2005. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/1820.

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

Council of Science Editors:

Basu S. Semi-supervised clustering: probabilistic models, algorithms and experiments. [Thesis]. University of Texas – Austin; 2005. Available from: http://hdl.handle.net/2152/1820

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


University of Texas – Austin

14. 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 (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 June 24, 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. 24 Jun 2019.

Vancouver:

Reisinger JS. Latent variable models of distributional lexical semantics. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Jun 24]. 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

15. -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 June 24, 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. 24 Jun 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 Jun 24]. 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

16. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Whang JJ. Overlapping community detection in massive social networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 24]. 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

17. 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 (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 June 24, 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. 24 Jun 2019.

Vancouver:

Chen C. Learning human activities and poses with interconnected data sources. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Jun 24]. 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

18. Melville, Prem Noel. Creating diverse ensemble classifiers to reduce supervision.

Degree: Computer Sciences, 2005, University of Texas – Austin

 Ensemble methods like Bagging and Boosting which combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Melville, P. N. (2005). Creating diverse ensemble classifiers to reduce supervision. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/2295

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):

Melville, Prem Noel. “Creating diverse ensemble classifiers to reduce supervision.” 2005. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/2295.

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

MLA Handbook (7th Edition):

Melville, Prem Noel. “Creating diverse ensemble classifiers to reduce supervision.” 2005. Web. 24 Jun 2019.

Vancouver:

Melville PN. Creating diverse ensemble classifiers to reduce supervision. [Internet] [Thesis]. University of Texas – Austin; 2005. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/2295.

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

Council of Science Editors:

Melville PN. Creating diverse ensemble classifiers to reduce supervision. [Thesis]. University of Texas – Austin; 2005. Available from: http://hdl.handle.net/2152/2295

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


University of Texas – Austin

19. 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 June 24, 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. 24 Jun 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 Jun 24]. 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

20. Vijayanarasimhan, Sudheendra. Active visual category learning.

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

 Visual recognition research develops algorithms and representations to autonomously recognize visual entities such as objects, actions, and attributes. The traditional protocol involves manually collecting training… (more)

Subjects/Keywords: Artificial intelligence; Active learning; Object recognition; Object detection; Cost-sensitive learning; Multi-level learning; Budgeted learning; Large-scale active learning; Live learning; Machine learning; Visual recognition system

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APA (6th Edition):

Vijayanarasimhan, S. (2011). Active visual category learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

MLA Handbook (7th Edition):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Web. 24 Jun 2019.

Vancouver:

Vijayanarasimhan S. Active visual category learning. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

Council of Science Editors:

Vijayanarasimhan S. Active visual category learning. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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


University of Texas – Austin

21. Kong, Danxia. Collaborative information acquisition.

Degree: Information, Risk, and Operations Management (IROM), 2011, University of Texas – Austin

 Increasingly, predictive models are used to support routine business de- cisions and are integral to the strategic competitive business strategies for a wide range of… (more)

Subjects/Keywords: Active information acquisition; Active learning; Multiple-tasks active learning; Decision-centric active learning; Active machine learning

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

APA (6th Edition):

Kong, D. (2011). Collaborative information acquisition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4678

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):

Kong, Danxia. “Collaborative information acquisition.” 2011. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/ETD-UT-2011-12-4678.

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

MLA Handbook (7th Edition):

Kong, Danxia. “Collaborative information acquisition.” 2011. Web. 24 Jun 2019.

Vancouver:

Kong D. Collaborative information acquisition. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4678.

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

Council of Science Editors:

Kong D. Collaborative information acquisition. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4678

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


University of Texas – Austin

22. Tang, Lap Poon Rupert. Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining.

Degree: Computer Sciences, 2003, University of Texas – Austin

Subjects/Keywords: Logic programming; Natural language processing (Computer science); Data mining

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APA (6th Edition):

Tang, L. P. R. (2003). Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/986

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):

Tang, Lap Poon Rupert. “Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining.” 2003. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/986.

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

MLA Handbook (7th Edition):

Tang, Lap Poon Rupert. “Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining.” 2003. Web. 24 Jun 2019.

Vancouver:

Tang LPR. Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining. [Internet] [Thesis]. University of Texas – Austin; 2003. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/986.

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

Council of Science Editors:

Tang LPR. Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining. [Thesis]. University of Texas – Austin; 2003. Available from: http://hdl.handle.net/2152/986

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


University of Texas – Austin

23. Nahm, Un Yong. Text mining with information extraction.

Degree: Computer Sciences, 2004, University of Texas – Austin

Subjects/Keywords: Data mining; Natural language processing (Computer science)

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

APA (6th Edition):

Nahm, U. Y. (2004). Text mining with information extraction. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/1280

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):

Nahm, Un Yong. “Text mining with information extraction.” 2004. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/1280.

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

MLA Handbook (7th Edition):

Nahm, Un Yong. “Text mining with information extraction.” 2004. Web. 24 Jun 2019.

Vancouver:

Nahm UY. Text mining with information extraction. [Internet] [Thesis]. University of Texas – Austin; 2004. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/1280.

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

Council of Science Editors:

Nahm UY. Text mining with information extraction. [Thesis]. University of Texas – Austin; 2004. Available from: http://hdl.handle.net/2152/1280

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


University of Texas – Austin

24. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Jong NK. Structured exploration for reinforcement learning. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jun 24]. 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

25. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Roller SC. Identifying lexical relationships and entailments with distributional semantics. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Jun 24]. 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

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 June 24, 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. 24 Jun 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 Jun 24]. 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. 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 June 24, 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. 24 Jun 2019.

Vancouver:

Si, Si PD. Large-scale non-linear prediction with applications. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Jun 24]. 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

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

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 June 24, 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. 24 Jun 2019.

Vancouver:

Garrette DH. Inducing grammars from linguistic universals and realistic amounts of supervision. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 24]. 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

29. Palmer, Alexis Mary. Semi-automated annotation and active learning for language documentation.

Degree: Linguistics, 2009, University of Texas – Austin

 By the end of this century, half of the approximately 6000 extant languages will cease to be transmitted from one generation to the next. The… (more)

Subjects/Keywords: Active learning; Computational linguistics; Language documentation; Language endangerment; Uspanteko; Semi-automated annotation; Interlinear text; Annotator expertise

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

APA (6th Edition):

Palmer, A. M. (2009). Semi-automated annotation and active learning for language documentation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/19805

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):

Palmer, Alexis Mary. “Semi-automated annotation and active learning for language documentation.” 2009. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/19805.

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

MLA Handbook (7th Edition):

Palmer, Alexis Mary. “Semi-automated annotation and active learning for language documentation.” 2009. Web. 24 Jun 2019.

Vancouver:

Palmer AM. Semi-automated annotation and active learning for language documentation. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/19805.

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

Council of Science Editors:

Palmer AM. Semi-automated annotation and active learning for language documentation. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/19805

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

30. Vijaya Raghavan, Sindhu. Bayesian Logic Programs for plan recognition and machine reading.

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

 Several real world tasks involve data that is uncertain and relational in nature. Traditional approaches like first-order logic and probabilistic models either deal with structured… (more)

Subjects/Keywords: Bayesian Logic Programs; Statistical relational learning; Plan recognition; Abductive reasoning; Machine reading; Rule learning; Information extraction; BLPs; SRL; IE; BALPs; Bayesian Abductive Logic Programs

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

APA (6th Edition):

Vijaya Raghavan, S. (2012). Bayesian Logic Programs for plan recognition and machine reading. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/19544

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):

Vijaya Raghavan, Sindhu. “Bayesian Logic Programs for plan recognition and machine reading.” 2012. Thesis, University of Texas – Austin. Accessed June 24, 2019. http://hdl.handle.net/2152/19544.

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

MLA Handbook (7th Edition):

Vijaya Raghavan, Sindhu. “Bayesian Logic Programs for plan recognition and machine reading.” 2012. Web. 24 Jun 2019.

Vancouver:

Vijaya Raghavan S. Bayesian Logic Programs for plan recognition and machine reading. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Jun 24]. Available from: http://hdl.handle.net/2152/19544.

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

Council of Science Editors:

Vijaya Raghavan S. Bayesian Logic Programs for plan recognition and machine reading. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/19544

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

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