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You searched for subject:(Machine). Showing records 1 – 30 of 13150 total matches.

[1] [2] [3] [4] [5] … [439]

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Oregon State University

1. Liu, Liping. Machine Learning Methods for Computational Sustainability.

Degree: PhD, Computer Science, 2016, Oregon State University

 Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning… (more)

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

Liu, L. (2016). Machine Learning Methods for Computational Sustainability. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/59159

Chicago Manual of Style (16th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Doctoral Dissertation, Oregon State University. Accessed February 24, 2020. http://hdl.handle.net/1957/59159.

MLA Handbook (7th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Web. 24 Feb 2020.

Vancouver:

Liu L. Machine Learning Methods for Computational Sustainability. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1957/59159.

Council of Science Editors:

Liu L. Machine Learning Methods for Computational Sustainability. [Doctoral Dissertation]. Oregon State University; 2016. Available from: http://hdl.handle.net/1957/59159


Oregon State University

2. Vatturi, Pavan Kumar. Rare category detection using hierarchical mean shift.

Degree: MS, Computer Science, 2009, Oregon State University

 Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to identify statistically significant… (more)

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

Vatturi, P. K. (2009). Rare category detection using hierarchical mean shift. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/10191

Chicago Manual of Style (16th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Masters Thesis, Oregon State University. Accessed February 24, 2020. http://hdl.handle.net/1957/10191.

MLA Handbook (7th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Web. 24 Feb 2020.

Vancouver:

Vatturi PK. Rare category detection using hierarchical mean shift. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1957/10191.

Council of Science Editors:

Vatturi PK. Rare category detection using hierarchical mean shift. [Masters Thesis]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/10191


Oregon State University

3. Bao, Xinlong. Applying machine learning for prediction, recommendation, and integration.

Degree: PhD, Computer Science, 2009, Oregon State University

 This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research… (more)

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

Bao, X. (2009). Applying machine learning for prediction, recommendation, and integration. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/12549

Chicago Manual of Style (16th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Doctoral Dissertation, Oregon State University. Accessed February 24, 2020. http://hdl.handle.net/1957/12549.

MLA Handbook (7th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Web. 24 Feb 2020.

Vancouver:

Bao X. Applying machine learning for prediction, recommendation, and integration. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1957/12549.

Council of Science Editors:

Bao X. Applying machine learning for prediction, recommendation, and integration. [Doctoral Dissertation]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/12549


Ryerson University

4. Hussain, Fatima. Resource allocation in clustered M2M networks: a q-learning approach.

Degree: 2016, Ryerson University

Machine to machine (M2M) communication has received increasing attention in recent years. A M2M network exhibits salient features such as large number of machines/devices, low… (more)

Subjects/Keywords: Machine-to-machine communications; Algorithms

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

APA (6th Edition):

Hussain, F. (2016). Resource allocation in clustered M2M networks: a q-learning approach. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A5103

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):

Hussain, Fatima. “Resource allocation in clustered M2M networks: a q-learning approach.” 2016. Thesis, Ryerson University. Accessed February 24, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A5103.

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

MLA Handbook (7th Edition):

Hussain, Fatima. “Resource allocation in clustered M2M networks: a q-learning approach.” 2016. Web. 24 Feb 2020.

Vancouver:

Hussain F. Resource allocation in clustered M2M networks: a q-learning approach. [Internet] [Thesis]. Ryerson University; 2016. [cited 2020 Feb 24]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A5103.

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

Council of Science Editors:

Hussain F. Resource allocation in clustered M2M networks: a q-learning approach. [Thesis]. Ryerson University; 2016. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A5103

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


Ryerson University

5. Ferdouse, Lilatul. Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks.

Degree: 2015, Ryerson University

 Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for… (more)

Subjects/Keywords: Machine-to-machine communications

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

APA (6th Edition):

Ferdouse, L. (2015). Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A4677

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):

Ferdouse, Lilatul. “Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks.” 2015. Thesis, Ryerson University. Accessed February 24, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A4677.

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

MLA Handbook (7th Edition):

Ferdouse, Lilatul. “Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks.” 2015. Web. 24 Feb 2020.

Vancouver:

Ferdouse L. Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks. [Internet] [Thesis]. Ryerson University; 2015. [cited 2020 Feb 24]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4677.

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

Council of Science Editors:

Ferdouse L. Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4677

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


Oregon State University

6. Hooper, Samuel. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.

Degree: MS, Geography, 2017, Oregon State University

 Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and… (more)

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

Hooper, S. (2017). Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/60148

Chicago Manual of Style (16th Edition):

Hooper, Samuel. “Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.” 2017. Masters Thesis, Oregon State University. Accessed February 24, 2020. http://hdl.handle.net/1957/60148.

MLA Handbook (7th Edition):

Hooper, Samuel. “Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.” 2017. Web. 24 Feb 2020.

Vancouver:

Hooper S. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. [Internet] [Masters thesis]. Oregon State University; 2017. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1957/60148.

Council of Science Editors:

Hooper S. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. [Masters Thesis]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/60148

7. Goff, Mark Bryan. Machine to machine communication for physical security.

Degree: 2013, University of Tennessee – Chattanooga

 The objective of this study was to research the core principles of Machine to Machine (M2M) communications methodology and create a framework that can be… (more)

Subjects/Keywords: Machine-to-machine communications

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APA (6th Edition):

Goff, M. B. (2013). Machine to machine communication for physical security. (Thesis). University of Tennessee – Chattanooga. Retrieved from https://scholar.utc.edu/theses/276

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):

Goff, Mark Bryan. “Machine to machine communication for physical security.” 2013. Thesis, University of Tennessee – Chattanooga. Accessed February 24, 2020. https://scholar.utc.edu/theses/276.

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

MLA Handbook (7th Edition):

Goff, Mark Bryan. “Machine to machine communication for physical security.” 2013. Web. 24 Feb 2020.

Vancouver:

Goff MB. Machine to machine communication for physical security. [Internet] [Thesis]. University of Tennessee – Chattanooga; 2013. [cited 2020 Feb 24]. Available from: https://scholar.utc.edu/theses/276.

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

Council of Science Editors:

Goff MB. Machine to machine communication for physical security. [Thesis]. University of Tennessee – Chattanooga; 2013. Available from: https://scholar.utc.edu/theses/276

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


University of Georgia

8. U, Man Chon. Improving learning outcomes by using clustering validity analysis to reduce label uncertainty.

Degree: PhD, Computer Science, 2013, University of Georgia

 When people make critical decisions, they often consider the opinions of multiple experts from different domains rather than committing themselves to a single expert or… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

U, M. C. (2013). Improving learning outcomes by using clustering validity analysis to reduce label uncertainty. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd

Chicago Manual of Style (16th Edition):

U, Man Chon. “Improving learning outcomes by using clustering validity analysis to reduce label uncertainty.” 2013. Doctoral Dissertation, University of Georgia. Accessed February 24, 2020. http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd.

MLA Handbook (7th Edition):

U, Man Chon. “Improving learning outcomes by using clustering validity analysis to reduce label uncertainty.” 2013. Web. 24 Feb 2020.

Vancouver:

U MC. Improving learning outcomes by using clustering validity analysis to reduce label uncertainty. [Internet] [Doctoral dissertation]. University of Georgia; 2013. [cited 2020 Feb 24]. Available from: http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd.

Council of Science Editors:

U MC. Improving learning outcomes by using clustering validity analysis to reduce label uncertainty. [Doctoral Dissertation]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd


University of Georgia

9. Richardson, William Dale. Evolutionary instance resampling for difficult data sets.

Degree: MS, Artificial Intelligence, 2013, University of Georgia

 In the field of machine learning, properties of data sets such as class imbalance and overlap often pose difficulties for classifier algorithms. A number of… (more)

Subjects/Keywords: machine learning

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

APA (6th Edition):

Richardson, W. D. (2013). Evolutionary instance resampling for difficult data sets. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms

Chicago Manual of Style (16th Edition):

Richardson, William Dale. “Evolutionary instance resampling for difficult data sets.” 2013. Masters Thesis, University of Georgia. Accessed February 24, 2020. http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms.

MLA Handbook (7th Edition):

Richardson, William Dale. “Evolutionary instance resampling for difficult data sets.” 2013. Web. 24 Feb 2020.

Vancouver:

Richardson WD. Evolutionary instance resampling for difficult data sets. [Internet] [Masters thesis]. University of Georgia; 2013. [cited 2020 Feb 24]. Available from: http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms.

Council of Science Editors:

Richardson WD. Evolutionary instance resampling for difficult data sets. [Masters Thesis]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms


University of Edinburgh

10. Jehl, Laura Elisabeth. Machine Translation for Twitter.

Degree: 2010, University of Edinburgh

 We carried out a study in which we explored the feasibility of machine translation for Twitter for the language pair English and German. As a… (more)

Subjects/Keywords: machine translation

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APA (6th Edition):

Jehl, L. E. (2010). Machine Translation for Twitter. (Thesis). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/5317

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):

Jehl, Laura Elisabeth. “Machine Translation for Twitter.” 2010. Thesis, University of Edinburgh. Accessed February 24, 2020. http://hdl.handle.net/1842/5317.

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

MLA Handbook (7th Edition):

Jehl, Laura Elisabeth. “Machine Translation for Twitter.” 2010. Web. 24 Feb 2020.

Vancouver:

Jehl LE. Machine Translation for Twitter. [Internet] [Thesis]. University of Edinburgh; 2010. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1842/5317.

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

Council of Science Editors:

Jehl LE. Machine Translation for Twitter. [Thesis]. University of Edinburgh; 2010. Available from: http://hdl.handle.net/1842/5317

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


University of Georgia

11. Lyle, Arlo. Baseball prediction using ensemble learning.

Degree: MS, Artificial Intelligence, 2007, University of Georgia

 As the salaries of baseball players continue to skyrocket and with the ever-increasing popularity of fantasy baseball, the desire for more accurate predictions of players’… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Lyle, A. (2007). Baseball prediction using ensemble learning. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms

Chicago Manual of Style (16th Edition):

Lyle, Arlo. “Baseball prediction using ensemble learning.” 2007. Masters Thesis, University of Georgia. Accessed February 24, 2020. http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms.

MLA Handbook (7th Edition):

Lyle, Arlo. “Baseball prediction using ensemble learning.” 2007. Web. 24 Feb 2020.

Vancouver:

Lyle A. Baseball prediction using ensemble learning. [Internet] [Masters thesis]. University of Georgia; 2007. [cited 2020 Feb 24]. Available from: http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms.

Council of Science Editors:

Lyle A. Baseball prediction using ensemble learning. [Masters Thesis]. University of Georgia; 2007. Available from: http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms


University of Illinois – Urbana-Champaign

12. Cai, Deng. Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning.

Degree: PhD, Computer Science, 2009, University of Illinois – Urbana-Champaign

 Spectral methods have recently emerged as a powerful tool for dimensionality reduction and manifold learning. These methods use information contained in the eigenvectors of a… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Cai, D. (2009). Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/11702

Chicago Manual of Style (16th Edition):

Cai, Deng. “Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning.” 2009. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed February 24, 2020. http://hdl.handle.net/2142/11702.

MLA Handbook (7th Edition):

Cai, Deng. “Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning.” 2009. Web. 24 Feb 2020.

Vancouver:

Cai D. Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2009. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/2142/11702.

Council of Science Editors:

Cai D. Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2009. Available from: http://hdl.handle.net/2142/11702


University of Illinois – Urbana-Champaign

13. Jiang, Yiming. Improvements and augmentations to Learning Based Java: a Java based learning based programming language.

Degree: MS, Computer Science, 2016, University of Illinois – Urbana-Champaign

Machine Learning (ML) is the science that enables computers with the ability to learn without being explicitly programmed. ML is so pervasive today, with applications… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Jiang, Y. (2016). Improvements and augmentations to Learning Based Java: a Java based learning based programming language. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90827

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):

Jiang, Yiming. “Improvements and augmentations to Learning Based Java: a Java based learning based programming language.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed February 24, 2020. http://hdl.handle.net/2142/90827.

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

MLA Handbook (7th Edition):

Jiang, Yiming. “Improvements and augmentations to Learning Based Java: a Java based learning based programming language.” 2016. Web. 24 Feb 2020.

Vancouver:

Jiang Y. Improvements and augmentations to Learning Based Java: a Java based learning based programming language. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/2142/90827.

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

Council of Science Editors:

Jiang Y. Improvements and augmentations to Learning Based Java: a Java based learning based programming language. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90827

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

14. Khorshidi, Alireza. Methods and Theories in Atomistic Reaction Engineering.

Degree: School of Engineering, 2018, Brown University

 Electronic-structure calculations have provided us with in-depth understanding of chemical and physical phenomena in atomic and molecular scales. In particular, density functional theory has been… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Khorshidi, A. (2018). Methods and Theories in Atomistic Reaction Engineering. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792658/

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):

Khorshidi, Alireza. “Methods and Theories in Atomistic Reaction Engineering.” 2018. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792658/.

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

MLA Handbook (7th Edition):

Khorshidi, Alireza. “Methods and Theories in Atomistic Reaction Engineering.” 2018. Web. 24 Feb 2020.

Vancouver:

Khorshidi A. Methods and Theories in Atomistic Reaction Engineering. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792658/.

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

Council of Science Editors:

Khorshidi A. Methods and Theories in Atomistic Reaction Engineering. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792658/

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

15. Lee, Seungjoon. Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.

Degree: Department of Applied Mathematics, 2017, Brown University

 For more than a decade, remarkable scientific progress in computational fluid dynamics (CFD) has been achieved via powerful collection of tools for exascale simulations, data-driven… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Lee, S. (2017). Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733405/

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

Chicago Manual of Style (16th Edition):

Lee, Seungjoon. “Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.” 2017. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:733405/.

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

MLA Handbook (7th Edition):

Lee, Seungjoon. “Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.” 2017. Web. 24 Feb 2020.

Vancouver:

Lee S. Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:733405/.

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

Council of Science Editors:

Lee S. Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733405/

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

16. Brawner, Stephen Andrew. Algorithms for the Personalization of AI for Robots and the Smart Home.

Degree: Department of Computer Science, 2018, Brown University

 Just as an interconnected-computerized world has produced large amounts of data resulting in exciting challenges for machine learning, connected households with robots and smart devices… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Brawner, S. A. (2018). Algorithms for the Personalization of AI for Robots and the Smart Home. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792905/

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):

Brawner, Stephen Andrew. “Algorithms for the Personalization of AI for Robots and the Smart Home.” 2018. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792905/.

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

MLA Handbook (7th Edition):

Brawner, Stephen Andrew. “Algorithms for the Personalization of AI for Robots and the Smart Home.” 2018. Web. 24 Feb 2020.

Vancouver:

Brawner SA. Algorithms for the Personalization of AI for Robots and the Smart Home. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792905/.

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

Council of Science Editors:

Brawner SA. Algorithms for the Personalization of AI for Robots and the Smart Home. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792905/

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

17. Wang, Yinong. Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.

Degree: Biomedical Engineering, 2018, Brown University

 Recent machine learning techniques have become a powerful tool in a variety of tasks, including neural decoding. Artificial neural network models, particularly recurrent models, can… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Wang, Y. (2018). Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792720/

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

Chicago Manual of Style (16th Edition):

Wang, Yinong. “Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.” 2018. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792720/.

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

MLA Handbook (7th Edition):

Wang, Yinong. “Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.” 2018. Web. 24 Feb 2020.

Vancouver:

Wang Y. Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792720/.

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

Council of Science Editors:

Wang Y. Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792720/

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

18. Patil, Prerna. Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.

Degree: School of Engineering, 2017, Brown University

 We tackle the classical problem of predicting the relation between of C_L , C_D and C_P vs Reynolds number for flow over cylinder using the… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Patil, P. (2017). Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733471/

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):

Patil, Prerna. “Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.” 2017. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:733471/.

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

MLA Handbook (7th Edition):

Patil, Prerna. “Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.” 2017. Web. 24 Feb 2020.

Vancouver:

Patil P. Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:733471/.

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

Council of Science Editors:

Patil P. Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733471/

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

19. Loper, Jackson Hoy. Theory and Computation for Modern Probabilistic Models.

Degree: Department of Applied Mathematics, 2017, Brown University

 Modern probabilistic models involve computation and analysis in very high-dimensional spaces. Here we explore several of ways in which analysis of problems high dimensional spaces… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Loper, J. H. (2017). Theory and Computation for Modern Probabilistic Models. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733424/

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):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:733424/.

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

MLA Handbook (7th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Web. 24 Feb 2020.

Vancouver:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:733424/.

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

Council of Science Editors:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733424/

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

20. Chua, Jeroen. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.

Degree: Department of Computer Science, 2017, Brown University

 We propose a general-purpose probabilistic framework for scene understanding tasks. We show that several classical scene understanding tasks can be modeled and addressed under a… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Chua, J. (2017). Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792615/

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):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792615/.

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

MLA Handbook (7th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Web. 24 Feb 2020.

Vancouver:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792615/.

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

Council of Science Editors:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:792615/

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

21. Ren, Zhile. Semantic Three-Dimensional Understanding of Dynamic Scenes.

Degree: Department of Computer Science, 2018, Brown University

 We develop new representations and algorithms for three-dimensional (3D) scene understanding from images and videos. To model cluttered indoor scenes, we introduce object descriptors that… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Ren, Z. (2018). Semantic Three-Dimensional Understanding of Dynamic Scenes. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792891/

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):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792891/.

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

MLA Handbook (7th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Web. 24 Feb 2020.

Vancouver:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792891/.

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

Council of Science Editors:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792891/

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

22. Tang, Yu-Hang. Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.

Degree: Department of Applied Mathematics, 2017, Brown University

 This dissertation is composed around the subject of multiscale modeling of soft matter and biophysical systems with applications using large-scale computations. Specifically, it is expanded… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Tang, Y. (2017). Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792611/

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, Yu-Hang. “Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.” 2017. Thesis, Brown University. Accessed February 24, 2020. https://repository.library.brown.edu/studio/item/bdr:792611/.

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

MLA Handbook (7th Edition):

Tang, Yu-Hang. “Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.” 2017. Web. 24 Feb 2020.

Vancouver:

Tang Y. Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 24]. Available from: https://repository.library.brown.edu/studio/item/bdr:792611/.

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

Council of Science Editors:

Tang Y. Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:792611/

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


Penn State University

23. Gowda Aghalya Shyama Sundar, Deepika. Identifying Product Web Pages Using Support Vector Machines.

Degree: MS, Computer Science and Engineering, 2010, Penn State University

 Comparative online shopping tools allow users to compare similar products from different vendors. Despite the availability of a multitude of online retail web sites, there… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Gowda Aghalya Shyama Sundar, D. (2010). Identifying Product Web Pages Using Support Vector Machines. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/10299

Chicago Manual of Style (16th Edition):

Gowda Aghalya Shyama Sundar, Deepika. “Identifying Product Web Pages Using Support Vector Machines.” 2010. Masters Thesis, Penn State University. Accessed February 24, 2020. https://etda.libraries.psu.edu/catalog/10299.

MLA Handbook (7th Edition):

Gowda Aghalya Shyama Sundar, Deepika. “Identifying Product Web Pages Using Support Vector Machines.” 2010. Web. 24 Feb 2020.

Vancouver:

Gowda Aghalya Shyama Sundar D. Identifying Product Web Pages Using Support Vector Machines. [Internet] [Masters thesis]. Penn State University; 2010. [cited 2020 Feb 24]. Available from: https://etda.libraries.psu.edu/catalog/10299.

Council of Science Editors:

Gowda Aghalya Shyama Sundar D. Identifying Product Web Pages Using Support Vector Machines. [Masters Thesis]. Penn State University; 2010. Available from: https://etda.libraries.psu.edu/catalog/10299


University of California – San Diego

24. Gallagher, Patrick W. Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.

Degree: Cognitive Science, 2014, University of California – San Diego

 As machine learning has more closely interacted with optimization, the concept of convexity has loomed large. Two properties beyond simple convexity have received particularly close… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Gallagher, P. W. (2014). Operator Theory for Analysis of Convex Optimization Methods in Machine Learning. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/153375qt

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):

Gallagher, Patrick W. “Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.” 2014. Thesis, University of California – San Diego. Accessed February 24, 2020. http://www.escholarship.org/uc/item/153375qt.

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

MLA Handbook (7th Edition):

Gallagher, Patrick W. “Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.” 2014. Web. 24 Feb 2020.

Vancouver:

Gallagher PW. Operator Theory for Analysis of Convex Optimization Methods in Machine Learning. [Internet] [Thesis]. University of California – San Diego; 2014. [cited 2020 Feb 24]. Available from: http://www.escholarship.org/uc/item/153375qt.

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

Council of Science Editors:

Gallagher PW. Operator Theory for Analysis of Convex Optimization Methods in Machine Learning. [Thesis]. University of California – San Diego; 2014. Available from: http://www.escholarship.org/uc/item/153375qt

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


University of Victoria

25. Lam, Newman Ming Ki. Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies.

Degree: School of Public Administration, 2018, University of Victoria

 Research on machine learning has taken numerous different directions. The present study focussed on the microstructural characteristics of learning systems. It was postulated that learning… (more)

Subjects/Keywords: Machine learning

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

APA (6th Edition):

Lam, N. M. K. (2018). Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies. (Thesis). University of Victoria. Retrieved from https://dspace.library.uvic.ca//handle/1828/9498

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):

Lam, Newman Ming Ki. “Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies.” 2018. Thesis, University of Victoria. Accessed February 24, 2020. https://dspace.library.uvic.ca//handle/1828/9498.

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

MLA Handbook (7th Edition):

Lam, Newman Ming Ki. “Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies.” 2018. Web. 24 Feb 2020.

Vancouver:

Lam NMK. Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies. [Internet] [Thesis]. University of Victoria; 2018. [cited 2020 Feb 24]. Available from: https://dspace.library.uvic.ca//handle/1828/9498.

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

Council of Science Editors:

Lam NMK. Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies. [Thesis]. University of Victoria; 2018. Available from: https://dspace.library.uvic.ca//handle/1828/9498

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


University of Oxford

26. Bouchacourt, Diane. Task-oriented learning of structured probability distributions.

Degree: PhD, 2017, University of Oxford

Machine learning models automatically learn from historical data to predict unseen events. Such events are often represented as complex multi-dimensional structures. In many cases there… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Bouchacourt, D. (2017). Task-oriented learning of structured probability distributions. (Doctoral Dissertation). University of Oxford. Retrieved from https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819

Chicago Manual of Style (16th Edition):

Bouchacourt, Diane. “Task-oriented learning of structured probability distributions.” 2017. Doctoral Dissertation, University of Oxford. Accessed February 24, 2020. https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819.

MLA Handbook (7th Edition):

Bouchacourt, Diane. “Task-oriented learning of structured probability distributions.” 2017. Web. 24 Feb 2020.

Vancouver:

Bouchacourt D. Task-oriented learning of structured probability distributions. [Internet] [Doctoral dissertation]. University of Oxford; 2017. [cited 2020 Feb 24]. Available from: https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819.

Council of Science Editors:

Bouchacourt D. Task-oriented learning of structured probability distributions. [Doctoral Dissertation]. University of Oxford; 2017. Available from: https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819


Oregon State University

27. Das, Shubhomoy. Incorporating User Feedback into Machine Learning Systems.

Degree: PhD, 2017, Oregon State University

 Although machine learning systems are often effective in real-world applications, there are situations in which they can be even better when provided with some degree… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Das, S. (2017). Incorporating User Feedback into Machine Learning Systems. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/61580

Chicago Manual of Style (16th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Doctoral Dissertation, Oregon State University. Accessed February 24, 2020. http://hdl.handle.net/1957/61580.

MLA Handbook (7th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Web. 24 Feb 2020.

Vancouver:

Das S. Incorporating User Feedback into Machine Learning Systems. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/1957/61580.

Council of Science Editors:

Das S. Incorporating User Feedback into Machine Learning Systems. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/61580


University of Arizona

28. Jones, Quintina R. Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning .

Degree: 2018, University of Arizona

 The Joint Space Operations Center of the United States Strategic Command’s Joint Functional Component Command for Space is responsible for detecting, tracking, and identifying all… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Jones, Q. R. (2018). Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/631456

Chicago Manual of Style (16th Edition):

Jones, Quintina R. “Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning .” 2018. Doctoral Dissertation, University of Arizona. Accessed February 24, 2020. http://hdl.handle.net/10150/631456.

MLA Handbook (7th Edition):

Jones, Quintina R. “Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning .” 2018. Web. 24 Feb 2020.

Vancouver:

Jones QR. Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning . [Internet] [Doctoral dissertation]. University of Arizona; 2018. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/10150/631456.

Council of Science Editors:

Jones QR. Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning . [Doctoral Dissertation]. University of Arizona; 2018. Available from: http://hdl.handle.net/10150/631456


University of Debrecen

29. Tóbiás, István. Machine Translation .

Degree: DE – TEK – Bölcsészettudományi Kar, 2013, University of Debrecen

 MT is a field which grows dynamically, faster and faster with every day passing by, but it is still in its early stage. These engines… (more)

Subjects/Keywords: machine; translation

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APA (6th Edition):

Tóbiás, I. (2013). Machine Translation . (Thesis). University of Debrecen. Retrieved from http://hdl.handle.net/2437/166566

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):

Tóbiás, István. “Machine Translation .” 2013. Thesis, University of Debrecen. Accessed February 24, 2020. http://hdl.handle.net/2437/166566.

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

MLA Handbook (7th Edition):

Tóbiás, István. “Machine Translation .” 2013. Web. 24 Feb 2020.

Vancouver:

Tóbiás I. Machine Translation . [Internet] [Thesis]. University of Debrecen; 2013. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/2437/166566.

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

Council of Science Editors:

Tóbiás I. Machine Translation . [Thesis]. University of Debrecen; 2013. Available from: http://hdl.handle.net/2437/166566

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


University of Waikato

30. Han, Zhimeng. Smoothing in Probability Estimation Trees .

Degree: 2011, University of Waikato

 Classification learning is a type of supervised machine learning technique that uses a classification model (e.g. decision tree) to predict unknown class labels for previously… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Han, Z. (2011). Smoothing in Probability Estimation Trees . (Masters Thesis). University of Waikato. Retrieved from http://hdl.handle.net/10289/5701

Chicago Manual of Style (16th Edition):

Han, Zhimeng. “Smoothing in Probability Estimation Trees .” 2011. Masters Thesis, University of Waikato. Accessed February 24, 2020. http://hdl.handle.net/10289/5701.

MLA Handbook (7th Edition):

Han, Zhimeng. “Smoothing in Probability Estimation Trees .” 2011. Web. 24 Feb 2020.

Vancouver:

Han Z. Smoothing in Probability Estimation Trees . [Internet] [Masters thesis]. University of Waikato; 2011. [cited 2020 Feb 24]. Available from: http://hdl.handle.net/10289/5701.

Council of Science Editors:

Han Z. Smoothing in Probability Estimation Trees . [Masters Thesis]. University of Waikato; 2011. Available from: http://hdl.handle.net/10289/5701

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