Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(Machine learning model development). Showing records 1 – 30 of 145311 total matches.

[1] [2] [3] [4] [5] … [4844]

Search Limiters

Last 2 Years | English Only

Degrees

Languages

Country

▼ Search Limiters


University of Texas – Austin

1. Zheng, Hanyue. KKBox subscription prediction : an application of machine learning methods.

Degree: Statistics, 2018, University of Texas – Austin

 This report used datasets from a Kaggle competition which aims to develop machine learning models to predict if users of a music app called KKBox… (more)

Subjects/Keywords: Machine learning; Classification; Machine learning models; Machine learning model development; Machine learning classification models; Machine learning model performance

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Zheng, H. (2018). KKBox subscription prediction : an application of machine learning methods. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67638

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):

Zheng, Hanyue. “KKBox subscription prediction : an application of machine learning methods.” 2018. Thesis, University of Texas – Austin. Accessed August 17, 2019. http://hdl.handle.net/2152/67638.

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

MLA Handbook (7th Edition):

Zheng, Hanyue. “KKBox subscription prediction : an application of machine learning methods.” 2018. Web. 17 Aug 2019.

Vancouver:

Zheng H. KKBox subscription prediction : an application of machine learning methods. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/2152/67638.

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

Council of Science Editors:

Zheng H. KKBox subscription prediction : an application of machine learning methods. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/67638

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


University of Ontario Institute of Technology

2. Gillett, Jonathan. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.

Degree: 2016, University of Ontario Institute of Technology

 The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a… (more)

Subjects/Keywords: Bitcoin; Predictive model; Machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Gillett, J. (2016). Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/884

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):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Thesis, University of Ontario Institute of Technology. Accessed August 17, 2019. http://hdl.handle.net/10155/884.

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

MLA Handbook (7th Edition):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Web. 17 Aug 2019.

Vancouver:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Internet] [Thesis]. University of Ontario Institute of Technology; 2016. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/10155/884.

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

Council of Science Editors:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Thesis]. University of Ontario Institute of Technology; 2016. Available from: http://hdl.handle.net/10155/884

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


Florida Atlantic University

3. Weiss, Karl Robert. Design of a Test Framework for the Evaluation of Transfer Learning Algorithms.

Degree: 2017, Florida Atlantic University

Summary: A traditional machine learning environment is characterized by the training and testing data being drawn from the same domain, therefore, having similar distribution characteristics.… (more)

Subjects/Keywords: Dissertations, Academic  – Florida Atlantic University; Machine learning.; Algorithms.; Machine learning Development.

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Weiss, K. R. (2017). Design of a Test Framework for the Evaluation of Transfer Learning Algorithms. (Thesis). Florida Atlantic University. Retrieved from http://purl.flvc.org/fau/fd/FA00005016 ; (URL) http://purl.flvc.org/fau/fd/FA00005925

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):

Weiss, Karl Robert. “Design of a Test Framework for the Evaluation of Transfer Learning Algorithms.” 2017. Thesis, Florida Atlantic University. Accessed August 17, 2019. http://purl.flvc.org/fau/fd/FA00005016 ; (URL) http://purl.flvc.org/fau/fd/FA00005925.

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

MLA Handbook (7th Edition):

Weiss, Karl Robert. “Design of a Test Framework for the Evaluation of Transfer Learning Algorithms.” 2017. Web. 17 Aug 2019.

Vancouver:

Weiss KR. Design of a Test Framework for the Evaluation of Transfer Learning Algorithms. [Internet] [Thesis]. Florida Atlantic University; 2017. [cited 2019 Aug 17]. Available from: http://purl.flvc.org/fau/fd/FA00005016 ; (URL) http://purl.flvc.org/fau/fd/FA00005925.

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

Council of Science Editors:

Weiss KR. Design of a Test Framework for the Evaluation of Transfer Learning Algorithms. [Thesis]. Florida Atlantic University; 2017. Available from: http://purl.flvc.org/fau/fd/FA00005016 ; (URL) http://purl.flvc.org/fau/fd/FA00005925

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


Univerzitet u Beogradu

4. Vujičić, Tijana M. Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu.

Degree: Fakultet organizacionih nauka, 2018, Univerzitet u Beogradu

računarske nauke-softversko inženjerstvo / Computer science-Software Engineering

Predmet istraživanja ovog rada su modeli strukturne regresije, koji su dizajnirani da koriste veze između objekata prilikom predviđanja… (more)

Subjects/Keywords: intelligent systems; machine learning; structured regression; GCRF model; graphs; software development; software tool; open source software; software usability

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Vujičić, T. M. (2018). Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:18659/bdef:Content/get

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):

Vujičić, Tijana M. “Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu.” 2018. Thesis, Univerzitet u Beogradu. Accessed August 17, 2019. https://fedorabg.bg.ac.rs/fedora/get/o:18659/bdef:Content/get.

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

MLA Handbook (7th Edition):

Vujičić, Tijana M. “Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu.” 2018. Web. 17 Aug 2019.

Vancouver:

Vujičić TM. Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu. [Internet] [Thesis]. Univerzitet u Beogradu; 2018. [cited 2019 Aug 17]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:18659/bdef:Content/get.

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

Council of Science Editors:

Vujičić TM. Softverski alat za ispitivanje algoritama strukturne regresije bazirane na GCRF modelu. [Thesis]. Univerzitet u Beogradu; 2018. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:18659/bdef:Content/get

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


University of New South Wales

5. Chen, Yu. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Considerable research has been done on automatic extraction of salient features from human faces in images over the last 20 years. For many existing systems,… (more)

Subjects/Keywords: Particle Filter; Active Shape Model; Machine Learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Chen, Y. (2015). Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Chen, Yu. “Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.” 2015. Masters Thesis, University of New South Wales. Accessed August 17, 2019. http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true.

MLA Handbook (7th Edition):

Chen, Yu. “Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.” 2015. Web. 17 Aug 2019.

Vancouver:

Chen Y. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. [Internet] [Masters thesis]. University of New South Wales; 2015. [cited 2019 Aug 17]. Available from: http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true.

Council of Science Editors:

Chen Y. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. [Masters Thesis]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true


University of New South Wales

6. Liu, Xianghang. New Algorithms for Graphical Models and Their Applications in Learning.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Probabilistic graphical models bring together graph theory and probability theory in a powerful formalism for multivariate statistical modelling. Since many machine learning problems involve the… (more)

Subjects/Keywords: statistical inference; machine learning; graphical model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liu, X. (2015). New Algorithms for Graphical Models and Their Applications in Learning. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Doctoral Dissertation, University of New South Wales. Accessed August 17, 2019. http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

MLA Handbook (7th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Web. 17 Aug 2019.

Vancouver:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Internet] [Doctoral dissertation]. University of New South Wales; 2015. [cited 2019 Aug 17]. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

Council of Science Editors:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Doctoral Dissertation]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true


Boston University

7. Hersh, Jonathan Samuel. Applications of econometrics and machine learning to development and international economics.

Degree: PhD, Economics, 2017, Boston University

 In the first chapter, I explore whether features derived from high resolution satellite images of Sri Lanka are able to predict poverty or income at… (more)

Subjects/Keywords: Economics; Economic development; Machine learning; Poverty; Trade

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hersh, J. S. (2017). Applications of econometrics and machine learning to development and international economics. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/33048

Chicago Manual of Style (16th Edition):

Hersh, Jonathan Samuel. “Applications of econometrics and machine learning to development and international economics.” 2017. Doctoral Dissertation, Boston University. Accessed August 17, 2019. http://hdl.handle.net/2144/33048.

MLA Handbook (7th Edition):

Hersh, Jonathan Samuel. “Applications of econometrics and machine learning to development and international economics.” 2017. Web. 17 Aug 2019.

Vancouver:

Hersh JS. Applications of econometrics and machine learning to development and international economics. [Internet] [Doctoral dissertation]. Boston University; 2017. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/2144/33048.

Council of Science Editors:

Hersh JS. Applications of econometrics and machine learning to development and international economics. [Doctoral Dissertation]. Boston University; 2017. Available from: http://hdl.handle.net/2144/33048


University of Houston

8. -9498-6365. Robust Domain Adaptation Using Active Learning.

Degree: Computer Science, Department of, 2016, University of Houston

 Traditional machine learning algorithms assume training and test datasets are generated from the same underlying distribution, which is not true for most real-world datasets. As… (more)

Subjects/Keywords: Domain Adaptation; Active Learning, Machine Learning; Model Complexity

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

-9498-6365. (2016). Robust Domain Adaptation Using Active Learning. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3520

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):

-9498-6365. “Robust Domain Adaptation Using Active Learning.” 2016. Thesis, University of Houston. Accessed August 17, 2019. http://hdl.handle.net/10657/3520.

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):

-9498-6365. “Robust Domain Adaptation Using Active Learning.” 2016. Web. 17 Aug 2019.

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

Vancouver:

-9498-6365. Robust Domain Adaptation Using Active Learning. [Internet] [Thesis]. University of Houston; 2016. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/10657/3520.

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:

-9498-6365. Robust Domain Adaptation Using Active Learning. [Thesis]. University of Houston; 2016. Available from: http://hdl.handle.net/10657/3520

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 Wollongong

9. Yang, Jie. A machine learning paradigm based on sparse signal representation.

Degree: PhD, 2013, University of Wollongong

Machine learning has been extensively investigated over the last three decades for its capability to learn mapping of functions from patterns. Nowadays, machine learning(more)

Subjects/Keywords: sparse signal representation; compressed sensing; machine learning; model selection; dictionary learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Yang, J. (2013). A machine learning paradigm based on sparse signal representation. (Doctoral Dissertation). University of Wollongong. Retrieved from 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0906 ELECTRICAL AND ELECTRONIC ENGINEERING ; https://ro.uow.edu.au/theses/3898

Chicago Manual of Style (16th Edition):

Yang, Jie. “A machine learning paradigm based on sparse signal representation.” 2013. Doctoral Dissertation, University of Wollongong. Accessed August 17, 2019. 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0906 ELECTRICAL AND ELECTRONIC ENGINEERING ; https://ro.uow.edu.au/theses/3898.

MLA Handbook (7th Edition):

Yang, Jie. “A machine learning paradigm based on sparse signal representation.” 2013. Web. 17 Aug 2019.

Vancouver:

Yang J. A machine learning paradigm based on sparse signal representation. [Internet] [Doctoral dissertation]. University of Wollongong; 2013. [cited 2019 Aug 17]. Available from: 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0906 ELECTRICAL AND ELECTRONIC ENGINEERING ; https://ro.uow.edu.au/theses/3898.

Council of Science Editors:

Yang J. A machine learning paradigm based on sparse signal representation. [Doctoral Dissertation]. University of Wollongong; 2013. Available from: 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0906 ELECTRICAL AND ELECTRONIC ENGINEERING ; https://ro.uow.edu.au/theses/3898


University of Connecticut

10. zhao, xiaojun. Machine Learning Approaches to 3D Model Classification.

Degree: MS, Mechanical Engineering, 2015, University of Connecticut

  A desirable 3D model classification system should be equipped with qualities such as highly correct classification accuracy, good enough classification speed, robustness to model(more)

Subjects/Keywords: 3D model; Classification; Machine learning; Shape Descriptors; Supervised Learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

zhao, x. (2015). Machine Learning Approaches to 3D Model Classification. (Masters Thesis). University of Connecticut. Retrieved from https://opencommons.uconn.edu/gs_theses/820

Chicago Manual of Style (16th Edition):

zhao, xiaojun. “Machine Learning Approaches to 3D Model Classification.” 2015. Masters Thesis, University of Connecticut. Accessed August 17, 2019. https://opencommons.uconn.edu/gs_theses/820.

MLA Handbook (7th Edition):

zhao, xiaojun. “Machine Learning Approaches to 3D Model Classification.” 2015. Web. 17 Aug 2019.

Vancouver:

zhao x. Machine Learning Approaches to 3D Model Classification. [Internet] [Masters thesis]. University of Connecticut; 2015. [cited 2019 Aug 17]. Available from: https://opencommons.uconn.edu/gs_theses/820.

Council of Science Editors:

zhao x. Machine Learning Approaches to 3D Model Classification. [Masters Thesis]. University of Connecticut; 2015. Available from: https://opencommons.uconn.edu/gs_theses/820


Washington University in St. Louis

11. Kusner, Matt J. Learning in the Real World: Constraints on Cost, Space, and Privacy.

Degree: PhD, Computer Science & Engineering, 2016, Washington University in St. Louis

  The sheer demand for machine learning in fields as varied as: healthcare, web-search ranking, factory automation, collision prediction, spam filtering, and many others, frequently… (more)

Subjects/Keywords: budgeted learning; differential privacy; machine learning; model compression; resource efficient learning; Computer Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Kusner, M. J. (2016). Learning in the Real World: Constraints on Cost, Space, and Privacy. (Doctoral Dissertation). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/eng_etds/305

Chicago Manual of Style (16th Edition):

Kusner, Matt J. “Learning in the Real World: Constraints on Cost, Space, and Privacy.” 2016. Doctoral Dissertation, Washington University in St. Louis. Accessed August 17, 2019. https://openscholarship.wustl.edu/eng_etds/305.

MLA Handbook (7th Edition):

Kusner, Matt J. “Learning in the Real World: Constraints on Cost, Space, and Privacy.” 2016. Web. 17 Aug 2019.

Vancouver:

Kusner MJ. Learning in the Real World: Constraints on Cost, Space, and Privacy. [Internet] [Doctoral dissertation]. Washington University in St. Louis; 2016. [cited 2019 Aug 17]. Available from: https://openscholarship.wustl.edu/eng_etds/305.

Council of Science Editors:

Kusner MJ. Learning in the Real World: Constraints on Cost, Space, and Privacy. [Doctoral Dissertation]. Washington University in St. Louis; 2016. Available from: https://openscholarship.wustl.edu/eng_etds/305


RMIT University

12. Manso, S. Support vector regression of a high fidelity helicopter flight model.

Degree: 2008, RMIT University

 The traditional technique for the dynamic modelling of helicopters and their systems involves the collection of flight data and aircraft specifications from which physics-based theoretical… (more)

Subjects/Keywords: Fields of Research; Helicopter; Support Vector Machine; Simulation; Servo flap; Flight Model; Seasprite; Machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Manso, S. (2008). Support vector regression of a high fidelity helicopter flight model. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:160076

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):

Manso, S. “Support vector regression of a high fidelity helicopter flight model.” 2008. Thesis, RMIT University. Accessed August 17, 2019. http://researchbank.rmit.edu.au/view/rmit:160076.

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

MLA Handbook (7th Edition):

Manso, S. “Support vector regression of a high fidelity helicopter flight model.” 2008. Web. 17 Aug 2019.

Vancouver:

Manso S. Support vector regression of a high fidelity helicopter flight model. [Internet] [Thesis]. RMIT University; 2008. [cited 2019 Aug 17]. Available from: http://researchbank.rmit.edu.au/view/rmit:160076.

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

Council of Science Editors:

Manso S. Support vector regression of a high fidelity helicopter flight model. [Thesis]. RMIT University; 2008. Available from: http://researchbank.rmit.edu.au/view/rmit:160076

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

13. Fu, Teng. IntelliChair: a non-intrusive sitting posture and sitting activity recognition system.

Degree: Doctoral Thesis, Computing and Maths, 2015, Abertay University

 Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily… (more)

Subjects/Keywords: Hidden Markov Model; Support Vector Machine; Pressure sensing; Machine learning; Activity recognition; Sitting posture classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Fu, T. (2015). IntelliChair: a non-intrusive sitting posture and sitting activity recognition system. (Thesis). Abertay University. Retrieved from https://rke.abertay.ac.uk/en/studentTheses/5b60a500-c3fc-4a79-9028-d7909e01b78c

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):

Fu, Teng. “IntelliChair: a non-intrusive sitting posture and sitting activity recognition system.” 2015. Thesis, Abertay University. Accessed August 17, 2019. https://rke.abertay.ac.uk/en/studentTheses/5b60a500-c3fc-4a79-9028-d7909e01b78c.

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

MLA Handbook (7th Edition):

Fu, Teng. “IntelliChair: a non-intrusive sitting posture and sitting activity recognition system.” 2015. Web. 17 Aug 2019.

Vancouver:

Fu T. IntelliChair: a non-intrusive sitting posture and sitting activity recognition system. [Internet] [Thesis]. Abertay University; 2015. [cited 2019 Aug 17]. Available from: https://rke.abertay.ac.uk/en/studentTheses/5b60a500-c3fc-4a79-9028-d7909e01b78c.

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

Council of Science Editors:

Fu T. IntelliChair: a non-intrusive sitting posture and sitting activity recognition system. [Thesis]. Abertay University; 2015. Available from: https://rke.abertay.ac.uk/en/studentTheses/5b60a500-c3fc-4a79-9028-d7909e01b78c

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


Oregon State University

14. 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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

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 August 17, 2019. http://hdl.handle.net/1957/10191.

MLA Handbook (7th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Web. 17 Aug 2019.

Vancouver:

Vatturi PK. Rare category detection using hierarchical mean shift. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2019 Aug 17]. 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

15. 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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

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 August 17, 2019. http://hdl.handle.net/1957/12549.

MLA Handbook (7th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Web. 17 Aug 2019.

Vancouver:

Bao X. Applying machine learning for prediction, recommendation, and integration. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2019 Aug 17]. 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


Oregon State University

16. 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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

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 August 17, 2019. http://hdl.handle.net/1957/59159.

MLA Handbook (7th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Web. 17 Aug 2019.

Vancouver:

Liu L. Machine Learning Methods for Computational Sustainability. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2019 Aug 17]. 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

17. 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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

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 August 17, 2019. 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. 17 Aug 2019.

Vancouver:

Hooper S. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. [Internet] [Masters thesis]. Oregon State University; 2017. [cited 2019 Aug 17]. 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


University of Utah

18. Seyedhosseini, Mojtaba. Scene labeling with supervised contextual models.

Degree: PhD, Electrical & Computer Engineering, 2014, University of Utah

 Scene labeling is the problem of assigning an object label to each pixel of a given image. It is the primary step towards image understanding… (more)

Subjects/Keywords: Computer vision; Connectome; Contextual model; Machine learning; Scene labeling

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Seyedhosseini, M. (2014). Scene labeling with supervised contextual models. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3190/rec/2135

Chicago Manual of Style (16th Edition):

Seyedhosseini, Mojtaba. “Scene labeling with supervised contextual models.” 2014. Doctoral Dissertation, University of Utah. Accessed August 17, 2019. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3190/rec/2135.

MLA Handbook (7th Edition):

Seyedhosseini, Mojtaba. “Scene labeling with supervised contextual models.” 2014. Web. 17 Aug 2019.

Vancouver:

Seyedhosseini M. Scene labeling with supervised contextual models. [Internet] [Doctoral dissertation]. University of Utah; 2014. [cited 2019 Aug 17]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3190/rec/2135.

Council of Science Editors:

Seyedhosseini M. Scene labeling with supervised contextual models. [Doctoral Dissertation]. University of Utah; 2014. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3190/rec/2135


University of Alberta

19. Eastman, Thomas. A disease classifier for metabolic profiles based on metabolic pathway knowledge.

Degree: MS, Department of Computing Science, 2010, University of Alberta

 This thesis presents Pathway Informed Analysis (PIA), a classification method for predicting disease states (diagnosis) from metabolic profile measurements that incorporates biological knowledge in the… (more)

Subjects/Keywords: metabolic profile; cachexia; graphical model; machine learning; metabolic pathway

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Eastman, T. (2010). A disease classifier for metabolic profiles based on metabolic pathway knowledge. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/fx719n29m

Chicago Manual of Style (16th Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Masters Thesis, University of Alberta. Accessed August 17, 2019. https://era.library.ualberta.ca/files/fx719n29m.

MLA Handbook (7th Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Web. 17 Aug 2019.

Vancouver:

Eastman T. A disease classifier for metabolic profiles based on metabolic pathway knowledge. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2019 Aug 17]. Available from: https://era.library.ualberta.ca/files/fx719n29m.

Council of Science Editors:

Eastman T. A disease classifier for metabolic profiles based on metabolic pathway knowledge. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/fx719n29m


University of Alberta

20. Xiao, Chenjun. Factorization Ranking Model for Fast Move Prediction in the Game of Go.

Degree: MS, Department of Computing Science, 2016, University of Alberta

 In this thesis, we investigate the move prediction problem in the game of Go by proposing a new ranking model named Factorization Bradley Terry (FBT)… (more)

Subjects/Keywords: Computer Go, Move Prediction, Machine Learning, Ranking Model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Xiao, C. (2016). Factorization Ranking Model for Fast Move Prediction in the Game of Go. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cx346d4457

Chicago Manual of Style (16th Edition):

Xiao, Chenjun. “Factorization Ranking Model for Fast Move Prediction in the Game of Go.” 2016. Masters Thesis, University of Alberta. Accessed August 17, 2019. https://era.library.ualberta.ca/files/cx346d4457.

MLA Handbook (7th Edition):

Xiao, Chenjun. “Factorization Ranking Model for Fast Move Prediction in the Game of Go.” 2016. Web. 17 Aug 2019.

Vancouver:

Xiao C. Factorization Ranking Model for Fast Move Prediction in the Game of Go. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2019 Aug 17]. Available from: https://era.library.ualberta.ca/files/cx346d4457.

Council of Science Editors:

Xiao C. Factorization Ranking Model for Fast Move Prediction in the Game of Go. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/cx346d4457


University of Kansas

21. Senf, Alexander J. A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS.

Degree: PhD, Electrical Engineering & Computer Science, 2011, University of Kansas

 Microarray technology captures the rate of expression of genes under varying experimental conditions. Genes encode the information necessary to build proteins; proteins used by cellular… (more)

Subjects/Keywords: Bioinformatics; Computer science; Hidden Markov model; Hmm; Machine learning; Microarray

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Senf, A. J. (2011). A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/7639

Chicago Manual of Style (16th Edition):

Senf, Alexander J. “A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS.” 2011. Doctoral Dissertation, University of Kansas. Accessed August 17, 2019. http://hdl.handle.net/1808/7639.

MLA Handbook (7th Edition):

Senf, Alexander J. “A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS.” 2011. Web. 17 Aug 2019.

Vancouver:

Senf AJ. A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS. [Internet] [Doctoral dissertation]. University of Kansas; 2011. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/1808/7639.

Council of Science Editors:

Senf AJ. A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS. [Doctoral Dissertation]. University of Kansas; 2011. Available from: http://hdl.handle.net/1808/7639


Queensland University of Technology

22. Wang, Hao Xing. Developing and testing readability measurements for second language learners.

Degree: 2016, Queensland University of Technology

 This research constructed a readability measurement for French speakers who view English as a second language. It identified the true cognates, which are the similar… (more)

Subjects/Keywords: Readability Assessment; Cognate Identification; Multilingual lexical; Machine Learning; Statistical Language Model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wang, H. X. (2016). Developing and testing readability measurements for second language learners. (Thesis). Queensland University of Technology. Retrieved from http://eprints.qut.edu.au/95111/

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, Hao Xing. “Developing and testing readability measurements for second language learners.” 2016. Thesis, Queensland University of Technology. Accessed August 17, 2019. http://eprints.qut.edu.au/95111/.

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

MLA Handbook (7th Edition):

Wang, Hao Xing. “Developing and testing readability measurements for second language learners.” 2016. Web. 17 Aug 2019.

Vancouver:

Wang HX. Developing and testing readability measurements for second language learners. [Internet] [Thesis]. Queensland University of Technology; 2016. [cited 2019 Aug 17]. Available from: http://eprints.qut.edu.au/95111/.

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

Council of Science Editors:

Wang HX. Developing and testing readability measurements for second language learners. [Thesis]. Queensland University of Technology; 2016. Available from: http://eprints.qut.edu.au/95111/

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


Louisiana State University

23. Khatami, Zahra. Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications.

Degree: PhD, Other Computer Engineering, 2017, Louisiana State University

  The compiler is able to detect the data dependencies in an application and is able to analyze the specific sections of code for parallelization… (more)

Subjects/Keywords: Runtime system; HPX; Compiler; Clang; Machine learning; Regression model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Khatami, Z. (2017). Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications. (Doctoral Dissertation). Louisiana State University. Retrieved from https://digitalcommons.lsu.edu/gradschool_dissertations/4091

Chicago Manual of Style (16th Edition):

Khatami, Zahra. “Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications.” 2017. Doctoral Dissertation, Louisiana State University. Accessed August 17, 2019. https://digitalcommons.lsu.edu/gradschool_dissertations/4091.

MLA Handbook (7th Edition):

Khatami, Zahra. “Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications.” 2017. Web. 17 Aug 2019.

Vancouver:

Khatami Z. Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications. [Internet] [Doctoral dissertation]. Louisiana State University; 2017. [cited 2019 Aug 17]. Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/4091.

Council of Science Editors:

Khatami Z. Compiler and Runtime Optimization Techniques for Implementation Scalable Parallel Applications. [Doctoral Dissertation]. Louisiana State University; 2017. Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/4091


UCLA

24. Gu, Shihao. Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques.

Degree: Statistics, 2017, UCLA

 We propose multiple advanced learning methods to deal with the "curse of dimensionality"challenge in the cross-sectional stock returns. Our purpose is to predict the one-month-aheadstock… (more)

Subjects/Keywords: Statistics; Finance; Factor Model; Firm Characteristics; Machine Learning; Market Return

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Gu, S. (2017). Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1jv8d4bc

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):

Gu, Shihao. “Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques.” 2017. Thesis, UCLA. Accessed August 17, 2019. http://www.escholarship.org/uc/item/1jv8d4bc.

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

MLA Handbook (7th Edition):

Gu, Shihao. “Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques.” 2017. Web. 17 Aug 2019.

Vancouver:

Gu S. Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques. [Internet] [Thesis]. UCLA; 2017. [cited 2019 Aug 17]. Available from: http://www.escholarship.org/uc/item/1jv8d4bc.

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

Council of Science Editors:

Gu S. Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/1jv8d4bc

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


University of Manchester

25. Mo, Yuanhan. TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS.

Degree: 2016, University of Manchester

Identifying relevant studies for inclusion in a systematic review (i.e. screening) is a complex, laborious and expensive task. Recently, a number of studies have shown… (more)

Subjects/Keywords: Topic model; Text Mining; Machine learning; Systematic Review

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Mo, Y. (2016). TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:300195

Chicago Manual of Style (16th Edition):

Mo, Yuanhan. “TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS.” 2016. Doctoral Dissertation, University of Manchester. Accessed August 17, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:300195.

MLA Handbook (7th Edition):

Mo, Yuanhan. “TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS.” 2016. Web. 17 Aug 2019.

Vancouver:

Mo Y. TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2019 Aug 17]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:300195.

Council of Science Editors:

Mo Y. TOPIC MODELLING FOR SUPPORTING SYSTEMATIC REVIEWS. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:300195

26. Hu, Xiaotong. Support Vector Machine and Its Application to Regression and Classification.

Degree: MSin Mathematics, Mathematics, 2017, Missouri State University

 Support Vector machine is currently a hot topic in the statistical learning area and is now widely used in data classification and regression modeling. In… (more)

Subjects/Keywords: support vector machine; data classification; regression model; hyperplane; statistical learning; Mathematics

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hu, X. (2017). Support Vector Machine and Its Application to Regression and Classification. (Masters Thesis). Missouri State University. Retrieved from https://bearworks.missouristate.edu/theses/3177

Chicago Manual of Style (16th Edition):

Hu, Xiaotong. “Support Vector Machine and Its Application to Regression and Classification.” 2017. Masters Thesis, Missouri State University. Accessed August 17, 2019. https://bearworks.missouristate.edu/theses/3177.

MLA Handbook (7th Edition):

Hu, Xiaotong. “Support Vector Machine and Its Application to Regression and Classification.” 2017. Web. 17 Aug 2019.

Vancouver:

Hu X. Support Vector Machine and Its Application to Regression and Classification. [Internet] [Masters thesis]. Missouri State University; 2017. [cited 2019 Aug 17]. Available from: https://bearworks.missouristate.edu/theses/3177.

Council of Science Editors:

Hu X. Support Vector Machine and Its Application to Regression and Classification. [Masters Thesis]. Missouri State University; 2017. Available from: https://bearworks.missouristate.edu/theses/3177


Virginia Tech

27. Ngo, Khai Thoi. Stacking Ensemble for auto_ml.

Degree: MS, Electrical and Computer Engineering, 2018, Virginia Tech

Machine learning has been a subject undergoing intense study across many different industries and academic research areas. Companies and researchers have taken full advantages of… (more)

Subjects/Keywords: Machine Learning; Stacking Ensemble; Model Selection; Hyper-parameter optimization; auto_ml

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ngo, K. T. (2018). Stacking Ensemble for auto_ml. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83547

Chicago Manual of Style (16th Edition):

Ngo, Khai Thoi. “Stacking Ensemble for auto_ml.” 2018. Masters Thesis, Virginia Tech. Accessed August 17, 2019. http://hdl.handle.net/10919/83547.

MLA Handbook (7th Edition):

Ngo, Khai Thoi. “Stacking Ensemble for auto_ml.” 2018. Web. 17 Aug 2019.

Vancouver:

Ngo KT. Stacking Ensemble for auto_ml. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/10919/83547.

Council of Science Editors:

Ngo KT. Stacking Ensemble for auto_ml. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83547


Princeton University

28. Goer, Maximilian Andreas Hubertus. Synthetic Diversification, Smart Randomization, and Commodity Indexing .

Degree: PhD, 2015, Princeton University

 This thesis investigates the use of randomization in asset allocation, and introduces a dynamic commodity index. Randomizing asset holdings can lead to extra rebalancing gains,… (more)

Subjects/Keywords: Asset allocation; Commodities; Hidden Markov model; Machine learning; Randomization; Rebalancing gains

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Goer, M. A. H. (2015). Synthetic Diversification, Smart Randomization, and Commodity Indexing . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01dz010s44z

Chicago Manual of Style (16th Edition):

Goer, Maximilian Andreas Hubertus. “Synthetic Diversification, Smart Randomization, and Commodity Indexing .” 2015. Doctoral Dissertation, Princeton University. Accessed August 17, 2019. http://arks.princeton.edu/ark:/88435/dsp01dz010s44z.

MLA Handbook (7th Edition):

Goer, Maximilian Andreas Hubertus. “Synthetic Diversification, Smart Randomization, and Commodity Indexing .” 2015. Web. 17 Aug 2019.

Vancouver:

Goer MAH. Synthetic Diversification, Smart Randomization, and Commodity Indexing . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2019 Aug 17]. Available from: http://arks.princeton.edu/ark:/88435/dsp01dz010s44z.

Council of Science Editors:

Goer MAH. Synthetic Diversification, Smart Randomization, and Commodity Indexing . [Doctoral Dissertation]. Princeton University; 2015. Available from: http://arks.princeton.edu/ark:/88435/dsp01dz010s44z


Princeton University

29. Lin, Changle. Integrated Asset Allocation Strategies: Application to Institutional Investors .

Degree: PhD, 2016, Princeton University

 Investors with incomes from businesses need to make investment decisions in face of business decisions. Prominent examples include: sovereign wealth funds with state businesses, pension… (more)

Subjects/Keywords: asset allocation model; financial engineering; machine learning; real option; stochastic control

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lin, C. (2016). Integrated Asset Allocation Strategies: Application to Institutional Investors . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01j3860942b

Chicago Manual of Style (16th Edition):

Lin, Changle. “Integrated Asset Allocation Strategies: Application to Institutional Investors .” 2016. Doctoral Dissertation, Princeton University. Accessed August 17, 2019. http://arks.princeton.edu/ark:/88435/dsp01j3860942b.

MLA Handbook (7th Edition):

Lin, Changle. “Integrated Asset Allocation Strategies: Application to Institutional Investors .” 2016. Web. 17 Aug 2019.

Vancouver:

Lin C. Integrated Asset Allocation Strategies: Application to Institutional Investors . [Internet] [Doctoral dissertation]. Princeton University; 2016. [cited 2019 Aug 17]. Available from: http://arks.princeton.edu/ark:/88435/dsp01j3860942b.

Council of Science Editors:

Lin C. Integrated Asset Allocation Strategies: Application to Institutional Investors . [Doctoral Dissertation]. Princeton University; 2016. Available from: http://arks.princeton.edu/ark:/88435/dsp01j3860942b


Oklahoma State University

30. Ding, Yi. Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches.

Degree: School of Electrical & Computer Engineering, 2010, Oklahoma State University

 With the development of multimedia and internet technologies, there is a growing interest in video mining research that is to discover knowledge existing in the… (more)

Subjects/Keywords: discriminative; generative; graphical model; machine learning; sports video; video mining

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ding, Y. (2010). Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/7854

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):

Ding, Yi. “Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches.” 2010. Thesis, Oklahoma State University. Accessed August 17, 2019. http://hdl.handle.net/11244/7854.

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

MLA Handbook (7th Edition):

Ding, Yi. “Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches.” 2010. Web. 17 Aug 2019.

Vancouver:

Ding Y. Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches. [Internet] [Thesis]. Oklahoma State University; 2010. [cited 2019 Aug 17]. Available from: http://hdl.handle.net/11244/7854.

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

Council of Science Editors:

Ding Y. Probabilistic Graphic Models for Sports Video Mining: Hybrid Generative-discriminative Approaches. [Thesis]. Oklahoma State University; 2010. Available from: http://hdl.handle.net/11244/7854

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

[1] [2] [3] [4] [5] … [4844]

.