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You searched for subject:(unsupervised). Showing records 1 – 30 of 459 total matches.

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University of Georgia

1. Asiimwe, Stephen. Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda.

Degree: DrPH, Public Health, 2013, University of Georgia

 Background Knowledge of one’s HIV status is a critical step in the cascade of HIV care and prevention. Despite being available, many people at risk… (more)

Subjects/Keywords: Unsupervised

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

APA (6th Edition):

Asiimwe, S. (2013). Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda. (Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/asiimwe_stephen_201312_drph

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):

Asiimwe, Stephen. “Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda.” 2013. Thesis, University of Georgia. Accessed June 20, 2019. http://purl.galileo.usg.edu/uga_etd/asiimwe_stephen_201312_drph.

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

MLA Handbook (7th Edition):

Asiimwe, Stephen. “Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda.” 2013. Web. 20 Jun 2019.

Vancouver:

Asiimwe S. Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda. [Internet] [Thesis]. University of Georgia; 2013. [cited 2019 Jun 20]. Available from: http://purl.galileo.usg.edu/uga_etd/asiimwe_stephen_201312_drph.

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

Council of Science Editors:

Asiimwe S. Implementation effectiveness of HIV self-testing and preferences for HIV testing in Uganda. [Thesis]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/asiimwe_stephen_201312_drph

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


Université de Neuchâtel

2. Kocher, MIrco. Text clustering with styles.

Degree: 2017, Université de Neuchâtel

 Cette thèse présente le problème du regroupement d'auteurs formulé de la manière suivante : en partant d'un ensemble composé de <i>n</i> textes, le but est… (more)

Subjects/Keywords: unsupervised learning

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APA (6th Edition):

Kocher, M. (2017). Text clustering with styles. (Thesis). Université de Neuchâtel. Retrieved from http://doc.rero.ch/record/306696

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):

Kocher, MIrco. “Text clustering with styles.” 2017. Thesis, Université de Neuchâtel. Accessed June 20, 2019. http://doc.rero.ch/record/306696.

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

MLA Handbook (7th Edition):

Kocher, MIrco. “Text clustering with styles.” 2017. Web. 20 Jun 2019.

Vancouver:

Kocher M. Text clustering with styles. [Internet] [Thesis]. Université de Neuchâtel; 2017. [cited 2019 Jun 20]. Available from: http://doc.rero.ch/record/306696.

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

Council of Science Editors:

Kocher M. Text clustering with styles. [Thesis]. Université de Neuchâtel; 2017. Available from: http://doc.rero.ch/record/306696

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


Victoria University of Wellington

3. Butler-Yeoman, Tony. Learning to Disentangle the Complex Causes of Data.

Degree: 2017, Victoria University of Wellington

 The ability to extract and model the meaning in data has been key to the success of modern machine learning. Typically, data reflects a combination… (more)

Subjects/Keywords: Unsupervised; Machine; Learning

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APA (6th Edition):

Butler-Yeoman, T. (2017). Learning to Disentangle the Complex Causes of Data. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/6951

Chicago Manual of Style (16th Edition):

Butler-Yeoman, Tony. “Learning to Disentangle the Complex Causes of Data.” 2017. Masters Thesis, Victoria University of Wellington. Accessed June 20, 2019. http://hdl.handle.net/10063/6951.

MLA Handbook (7th Edition):

Butler-Yeoman, Tony. “Learning to Disentangle the Complex Causes of Data.” 2017. Web. 20 Jun 2019.

Vancouver:

Butler-Yeoman T. Learning to Disentangle the Complex Causes of Data. [Internet] [Masters thesis]. Victoria University of Wellington; 2017. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10063/6951.

Council of Science Editors:

Butler-Yeoman T. Learning to Disentangle the Complex Causes of Data. [Masters Thesis]. Victoria University of Wellington; 2017. Available from: http://hdl.handle.net/10063/6951

4. Hirayama, Jun-ichiro. Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: unsupervised learning

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

APA (6th Edition):

Hirayama, J. (n.d.). Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/4366

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hirayama, Jun-ichiro. “Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed June 20, 2019. http://hdl.handle.net/10061/4366.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hirayama, Jun-ichiro. “Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ.” Web. 20 Jun 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Hirayama J. Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10061/4366.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Hirayama J. Probabilistic approach to unsupervised representation learning in dynamic environments : 動的環境における教師なし表現学習への確率的アプローチ; ドウテキ カンキョウ ニオケル キョウシ ナシ ヒョウゲン ガクシュウ エノ カクリツテキ アプローチ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/4366

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

5. Madokoro, Hirokazu. Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: Unsupervised learning

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

APA (6th Edition):

Madokoro, H. (n.d.). Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/6019

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Madokoro, Hirokazu. “Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed June 20, 2019. http://hdl.handle.net/10061/6019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Madokoro, Hirokazu. “Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ.” Web. 20 Jun 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Madokoro H. Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10061/6019.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Madokoro H. Unsupervised Category Formation and Its Applications to Robot Vision : 教師なしカテゴリ形成とロボットビジョンへの応用; キョウシ ナシ カテゴリ ケイセイ ト ロボット ビジョン エノ オウヨウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/6019

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


Penn State University

6. Jha, Manjari. Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection.

Degree: 2018, Penn State University

 This thesis focuses on developing probabilistic models for the analysis of diverse datasets using unsupervised clustering techniques. Primarily, we focus on two main fields: the… (more)

Subjects/Keywords: metagenomics; intrusion detection; clustering; unsupervised

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

APA (6th Edition):

Jha, M. (2018). Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection. (Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/15543mom5590

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):

Jha, Manjari. “Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection.” 2018. Thesis, Penn State University. Accessed June 20, 2019. https://etda.libraries.psu.edu/catalog/15543mom5590.

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

MLA Handbook (7th Edition):

Jha, Manjari. “Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection.” 2018. Web. 20 Jun 2019.

Vancouver:

Jha M. Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection. [Internet] [Thesis]. Penn State University; 2018. [cited 2019 Jun 20]. Available from: https://etda.libraries.psu.edu/catalog/15543mom5590.

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

Council of Science Editors:

Jha M. Probabilistic Techniques for Metagenomic Clustering and Intrusion Detection. [Thesis]. Penn State University; 2018. Available from: https://etda.libraries.psu.edu/catalog/15543mom5590

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


University of Alberta

7. White, Martha. Regularized factor models.

Degree: PhD, Department of Computing Science, 2014, University of Alberta

 This dissertation explores regularized factor models as a simple unification of machine learn- ing problems, with a focus on algorithmic development within this known formalism.… (more)

Subjects/Keywords: machine learning; artificial intelligence; unsupervised learning

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APA (6th Edition):

White, M. (2014). Regularized factor models. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/gq67jt70x

Chicago Manual of Style (16th Edition):

White, Martha. “Regularized factor models.” 2014. Doctoral Dissertation, University of Alberta. Accessed June 20, 2019. https://era.library.ualberta.ca/files/gq67jt70x.

MLA Handbook (7th Edition):

White, Martha. “Regularized factor models.” 2014. Web. 20 Jun 2019.

Vancouver:

White M. Regularized factor models. [Internet] [Doctoral dissertation]. University of Alberta; 2014. [cited 2019 Jun 20]. Available from: https://era.library.ualberta.ca/files/gq67jt70x.

Council of Science Editors:

White M. Regularized factor models. [Doctoral Dissertation]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/gq67jt70x


University of Guelph

8. Im, Jiwoong. Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems .

Degree: 2015, University of Guelph

 The objective of this thesis is to take the dynamical systems approach to understand the unsupervised learning models and learning algorithms. Gated auto-encoders (GAEs) are… (more)

Subjects/Keywords: Machine learning; Deep Learning; unsupervised learning

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APA (6th Edition):

Im, J. (2015). Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems . (Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8809

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):

Im, Jiwoong. “Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems .” 2015. Thesis, University of Guelph. Accessed June 20, 2019. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8809.

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

MLA Handbook (7th Edition):

Im, Jiwoong. “Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems .” 2015. Web. 20 Jun 2019.

Vancouver:

Im J. Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems . [Internet] [Thesis]. University of Guelph; 2015. [cited 2019 Jun 20]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8809.

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

Council of Science Editors:

Im J. Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems . [Thesis]. University of Guelph; 2015. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8809

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


California State University – San Bernardino

9. Miller, Benjamin Alan. Distance Effects in Similarity Based Free Categorization.

Degree: MAin General Experimental Psychology, Psychology, 2015, California State University – San Bernardino

  This experiment investigated the processes underlying similarity-based free categorization. Of particular interest was how temporal distance between similar objects affects the likelihood that people… (more)

Subjects/Keywords: Categorization; Unsupervised; Temporal; Distance; Labeling; Cognitive Psychology

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APA (6th Edition):

Miller, B. A. (2015). Distance Effects in Similarity Based Free Categorization. (Thesis). California State University – San Bernardino. Retrieved from http://scholarworks.lib.csusb.edu/etd/238

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):

Miller, Benjamin Alan. “Distance Effects in Similarity Based Free Categorization.” 2015. Thesis, California State University – San Bernardino. Accessed June 20, 2019. http://scholarworks.lib.csusb.edu/etd/238.

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

MLA Handbook (7th Edition):

Miller, Benjamin Alan. “Distance Effects in Similarity Based Free Categorization.” 2015. Web. 20 Jun 2019.

Vancouver:

Miller BA. Distance Effects in Similarity Based Free Categorization. [Internet] [Thesis]. California State University – San Bernardino; 2015. [cited 2019 Jun 20]. Available from: http://scholarworks.lib.csusb.edu/etd/238.

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

Council of Science Editors:

Miller BA. Distance Effects in Similarity Based Free Categorization. [Thesis]. California State University – San Bernardino; 2015. Available from: http://scholarworks.lib.csusb.edu/etd/238

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


University of Southern California

10. Deutsch, Shay. Learning the geometric structure of high dimensional data using the Tensor Voting Graph.

Degree: PhD, Computer Science, 2017, University of Southern California

 This study addresses a range of fundamental problems in unsupervised manifold learning. Given a set of noisy points in a high dimensional space that lie… (more)

Subjects/Keywords: manifold learning; unsupervised denoising; Tensor Voting Graph

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

APA (6th Edition):

Deutsch, S. (2017). Learning the geometric structure of high dimensional data using the Tensor Voting Graph. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/640839/rec/3787

Chicago Manual of Style (16th Edition):

Deutsch, Shay. “Learning the geometric structure of high dimensional data using the Tensor Voting Graph.” 2017. Doctoral Dissertation, University of Southern California. Accessed June 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/640839/rec/3787.

MLA Handbook (7th Edition):

Deutsch, Shay. “Learning the geometric structure of high dimensional data using the Tensor Voting Graph.” 2017. Web. 20 Jun 2019.

Vancouver:

Deutsch S. Learning the geometric structure of high dimensional data using the Tensor Voting Graph. [Internet] [Doctoral dissertation]. University of Southern California; 2017. [cited 2019 Jun 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/640839/rec/3787.

Council of Science Editors:

Deutsch S. Learning the geometric structure of high dimensional data using the Tensor Voting Graph. [Doctoral Dissertation]. University of Southern California; 2017. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/640839/rec/3787


Halmstad University

11. Grubinger, Thomas. Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods.

Degree: Computer and Electrical Engineering (IDE), 2008, Halmstad University

  The goal was to extract knowledge from data that is logged by the electronic system of every Volvo truck. This allowed the evaluation of… (more)

Subjects/Keywords: Unsupervised learning; logged vehicle data; Knowledge extraction

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

APA (6th Edition):

Grubinger, T. (2008). Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods. (Thesis). Halmstad University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1147

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):

Grubinger, Thomas. “Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods.” 2008. Thesis, Halmstad University. Accessed June 20, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1147.

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

MLA Handbook (7th Edition):

Grubinger, Thomas. “Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods.” 2008. Web. 20 Jun 2019.

Vancouver:

Grubinger T. Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods. [Internet] [Thesis]. Halmstad University; 2008. [cited 2019 Jun 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1147.

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

Council of Science Editors:

Grubinger T. Knowledge Extraction from Logged Truck Data using Unsupervised Learning Methods. [Thesis]. Halmstad University; 2008. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1147

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


University of Debrecen

12. Bod, Gergely. Self-taught learning: Implementation using MATLAB .

Degree: DE – TEK – Informatikai Kar, 2014, University of Debrecen

 Self-taught learning is a new framework in the domain of machine learning. It has the potential that by using unsupervised learning strategies to automatically learn… (more)

Subjects/Keywords: unsupervised learning; machine learning; neural network; autoencoder

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APA (6th Edition):

Bod, G. (2014). Self-taught learning: Implementation using MATLAB . (Thesis). University of Debrecen. Retrieved from http://hdl.handle.net/2437/178637

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):

Bod, Gergely. “Self-taught learning: Implementation using MATLAB .” 2014. Thesis, University of Debrecen. Accessed June 20, 2019. http://hdl.handle.net/2437/178637.

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

MLA Handbook (7th Edition):

Bod, Gergely. “Self-taught learning: Implementation using MATLAB .” 2014. Web. 20 Jun 2019.

Vancouver:

Bod G. Self-taught learning: Implementation using MATLAB . [Internet] [Thesis]. University of Debrecen; 2014. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/2437/178637.

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

Council of Science Editors:

Bod G. Self-taught learning: Implementation using MATLAB . [Thesis]. University of Debrecen; 2014. Available from: http://hdl.handle.net/2437/178637

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


University of Manchester

13. Rostamniakankalhori, Sharareh. Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course.

Degree: 2011, University of Manchester

 Tuberculosis (TB) is an infectious disease which is a global public health problem with over 9 million new cases annually. Tuberculosis treatment, with patient supervision… (more)

Subjects/Keywords: Integrated Supervised and Unsupervised Learning; Tuberculosis; plediction

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APA (6th Edition):

Rostamniakankalhori, S. (2011). Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:132404

Chicago Manual of Style (16th Edition):

Rostamniakankalhori, Sharareh. “Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course.” 2011. Doctoral Dissertation, University of Manchester. Accessed June 20, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:132404.

MLA Handbook (7th Edition):

Rostamniakankalhori, Sharareh. “Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course.” 2011. Web. 20 Jun 2019.

Vancouver:

Rostamniakankalhori S. Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course. [Internet] [Doctoral dissertation]. University of Manchester; 2011. [cited 2019 Jun 20]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:132404.

Council of Science Editors:

Rostamniakankalhori S. Integrated Supervised and Unsupervised Learning Method to Predict the Outcome of Tuberculosis Treatment Course. [Doctoral Dissertation]. University of Manchester; 2011. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:132404


University of Houston

14. Xu, Yan. Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets.

Degree: Electrical and Computer Engineering, Department of, 2015, University of Houston

 The goal of this dissertation is to develop unsupervised algorithms for discovering previously unknown subspace trends in massive multivariate biomedical data sets without the benefit… (more)

Subjects/Keywords: trend; visualization; biomedical; unsupervised learning; feature selection

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APA (6th Edition):

Xu, Y. (2015). Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3672

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):

Xu, Yan. “Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets.” 2015. Thesis, University of Houston. Accessed June 20, 2019. http://hdl.handle.net/10657/3672.

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

MLA Handbook (7th Edition):

Xu, Yan. “Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets.” 2015. Web. 20 Jun 2019.

Vancouver:

Xu Y. Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets. [Internet] [Thesis]. University of Houston; 2015. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10657/3672.

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

Council of Science Editors:

Xu Y. Unsupervised Discovery and Representation of Subspace Trends in Massive Biomedical Datasets. [Thesis]. University of Houston; 2015. Available from: http://hdl.handle.net/10657/3672

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

15. Zeltner, Felix. Autonomous Terrain Classification Through Unsupervised Learning.

Degree: Electrical and Space Engineering, 2016, Luleå University of Technology

  A key component of autonomous outdoor navigation in unstructured environments is the classification of terrain. Recent development in the area of machine learning show… (more)

Subjects/Keywords: Terrain Classification; Unsupervised Learning; Robotics; Neural Networks

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

APA (6th Edition):

Zeltner, F. (2016). Autonomous Terrain Classification Through Unsupervised Learning. (Thesis). Luleå University of Technology. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60893

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):

Zeltner, Felix. “Autonomous Terrain Classification Through Unsupervised Learning.” 2016. Thesis, Luleå University of Technology. Accessed June 20, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60893.

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

MLA Handbook (7th Edition):

Zeltner, Felix. “Autonomous Terrain Classification Through Unsupervised Learning.” 2016. Web. 20 Jun 2019.

Vancouver:

Zeltner F. Autonomous Terrain Classification Through Unsupervised Learning. [Internet] [Thesis]. Luleå University of Technology; 2016. [cited 2019 Jun 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60893.

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

Council of Science Editors:

Zeltner F. Autonomous Terrain Classification Through Unsupervised Learning. [Thesis]. Luleå University of Technology; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60893

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


University of Toronto

16. Makhzani, Alireza. Unsupervised Representation Learning with Autoencoders.

Degree: PhD, 2018, University of Toronto

 Despite the recent progress in machine learning and deep learning, unsupervised learning still remains a largely unsolved problem. It is widely recognized that unsupervised learning… (more)

Subjects/Keywords: Deep Learning; Machine Learning; Unsupervised Learning; 0984

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

APA (6th Edition):

Makhzani, A. (2018). Unsupervised Representation Learning with Autoencoders. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/89800

Chicago Manual of Style (16th Edition):

Makhzani, Alireza. “Unsupervised Representation Learning with Autoencoders.” 2018. Doctoral Dissertation, University of Toronto. Accessed June 20, 2019. http://hdl.handle.net/1807/89800.

MLA Handbook (7th Edition):

Makhzani, Alireza. “Unsupervised Representation Learning with Autoencoders.” 2018. Web. 20 Jun 2019.

Vancouver:

Makhzani A. Unsupervised Representation Learning with Autoencoders. [Internet] [Doctoral dissertation]. University of Toronto; 2018. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/1807/89800.

Council of Science Editors:

Makhzani A. Unsupervised Representation Learning with Autoencoders. [Doctoral Dissertation]. University of Toronto; 2018. Available from: http://hdl.handle.net/1807/89800


Iowa State University

17. Miller, Matthew Miller Adam. Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm.

Degree: 2009, Iowa State University

 In this thesis I suggest and evaluate an algorithm for the unsupervised segmentation of audio speech streams. Specific attention will be paid to the developmental… (more)

Subjects/Keywords: Audio; Segmentation; Speech; Unsupervised; Computer Sciences

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

APA (6th Edition):

Miller, M. M. A. (2009). Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/10725

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):

Miller, Matthew Miller Adam. “Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm.” 2009. Thesis, Iowa State University. Accessed June 20, 2019. https://lib.dr.iastate.edu/etd/10725.

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

MLA Handbook (7th Edition):

Miller, Matthew Miller Adam. “Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm.” 2009. Web. 20 Jun 2019.

Vancouver:

Miller MMA. Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm. [Internet] [Thesis]. Iowa State University; 2009. [cited 2019 Jun 20]. Available from: https://lib.dr.iastate.edu/etd/10725.

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

Council of Science Editors:

Miller MMA. Unsupervised Segmentation of Audio Speech Using the Voting Experts Algorithm. [Thesis]. Iowa State University; 2009. Available from: https://lib.dr.iastate.edu/etd/10725

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


Universidade Nova

18. Madsen, Jacob Hastrup. Outlier detection for improved clustering : empirical research for unsupervised data mining.

Degree: 2018, Universidade Nova

 Many clustering algorithms are sensitive to noise disturbing the results when trying to identify and characterize clusters in data. Due to the multidimensional nature of… (more)

Subjects/Keywords: Outlier Detection; Unsupervised Learning; Clustering; Data Mining

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APA (6th Edition):

Madsen, J. H. (2018). Outlier detection for improved clustering : empirical research for unsupervised data mining. (Thesis). Universidade Nova. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464

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):

Madsen, Jacob Hastrup. “Outlier detection for improved clustering : empirical research for unsupervised data mining.” 2018. Thesis, Universidade Nova. Accessed June 20, 2019. https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464.

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

MLA Handbook (7th Edition):

Madsen, Jacob Hastrup. “Outlier detection for improved clustering : empirical research for unsupervised data mining.” 2018. Web. 20 Jun 2019.

Vancouver:

Madsen JH. Outlier detection for improved clustering : empirical research for unsupervised data mining. [Internet] [Thesis]. Universidade Nova; 2018. [cited 2019 Jun 20]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464.

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

Council of Science Editors:

Madsen JH. Outlier detection for improved clustering : empirical research for unsupervised data mining. [Thesis]. Universidade Nova; 2018. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/34464

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


George Mason University

19. Wang, Pu. Nonparametric Bayesian Models for Unsupervised Learning .

Degree: 2011, George Mason University

Unsupervised learning is an important topic in machine learning. In particular, clustering is an unsupervised learning problem that arises in a variety of applications for… (more)

Subjects/Keywords: Unsupervised Learning; Clustering; Bayesian Nonparametrics; Clustering Ensembles

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APA (6th Edition):

Wang, P. (2011). Nonparametric Bayesian Models for Unsupervised Learning . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/6360

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, Pu. “Nonparametric Bayesian Models for Unsupervised Learning .” 2011. Thesis, George Mason University. Accessed June 20, 2019. http://hdl.handle.net/1920/6360.

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

MLA Handbook (7th Edition):

Wang, Pu. “Nonparametric Bayesian Models for Unsupervised Learning .” 2011. Web. 20 Jun 2019.

Vancouver:

Wang P. Nonparametric Bayesian Models for Unsupervised Learning . [Internet] [Thesis]. George Mason University; 2011. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/1920/6360.

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

Council of Science Editors:

Wang P. Nonparametric Bayesian Models for Unsupervised Learning . [Thesis]. George Mason University; 2011. Available from: http://hdl.handle.net/1920/6360

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


University of Texas – Austin

20. -6888-3095. Embodied learning for visual recognition.

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

 The field of visual recognition in recent years has come to rely on large expensively curated and manually labeled "bags of disembodied images". In the… (more)

Subjects/Keywords: Computer vision; Unsupervised learning; Embodied learning

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APA (6th Edition):

-6888-3095. (2017). Embodied learning for visual recognition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63489

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):

-6888-3095. “Embodied learning for visual recognition.” 2017. Thesis, University of Texas – Austin. Accessed June 20, 2019. http://hdl.handle.net/2152/63489.

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):

-6888-3095. “Embodied learning for visual recognition.” 2017. Web. 20 Jun 2019.

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

Vancouver:

-6888-3095. Embodied learning for visual recognition. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/2152/63489.

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:

-6888-3095. Embodied learning for visual recognition. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63489

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 Illinois – Urbana-Champaign

21. Riaz, Mehwish. An unsupervised approach to identifying causal relations from relevant scenarios.

Degree: MS, 0112, 2010, University of Illinois – Urbana-Champaign

 Semantic relations between various text units play an important role in natural language understanding, as key elements of text coherence. The automatic identification of these… (more)

Subjects/Keywords: Causality; Semantic Relations; Topics; Unsupervised Learning

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APA (6th Edition):

Riaz, M. (2010). An unsupervised approach to identifying causal relations from relevant scenarios. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/14759

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):

Riaz, Mehwish. “An unsupervised approach to identifying causal relations from relevant scenarios.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed June 20, 2019. http://hdl.handle.net/2142/14759.

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

MLA Handbook (7th Edition):

Riaz, Mehwish. “An unsupervised approach to identifying causal relations from relevant scenarios.” 2010. Web. 20 Jun 2019.

Vancouver:

Riaz M. An unsupervised approach to identifying causal relations from relevant scenarios. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/2142/14759.

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

Council of Science Editors:

Riaz M. An unsupervised approach to identifying causal relations from relevant scenarios. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/14759

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


University of Connecticut

22. Yankee, Tara N. Rank Aggregation of Feature Scoring Methods for Unsupervised Learning.

Degree: M. Eng., Biomedical Engineering, 2017, University of Connecticut

  The ability to collect and store large amounts of data is transforming data-driven discovery; recent technological advances in biology allow systematic data production and… (more)

Subjects/Keywords: clustering; ensemble learning; feature selection; unsupervised learning

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APA (6th Edition):

Yankee, T. N. (2017). Rank Aggregation of Feature Scoring Methods for Unsupervised Learning. (Masters Thesis). University of Connecticut. Retrieved from https://opencommons.uconn.edu/gs_theses/1123

Chicago Manual of Style (16th Edition):

Yankee, Tara N. “Rank Aggregation of Feature Scoring Methods for Unsupervised Learning.” 2017. Masters Thesis, University of Connecticut. Accessed June 20, 2019. https://opencommons.uconn.edu/gs_theses/1123.

MLA Handbook (7th Edition):

Yankee, Tara N. “Rank Aggregation of Feature Scoring Methods for Unsupervised Learning.” 2017. Web. 20 Jun 2019.

Vancouver:

Yankee TN. Rank Aggregation of Feature Scoring Methods for Unsupervised Learning. [Internet] [Masters thesis]. University of Connecticut; 2017. [cited 2019 Jun 20]. Available from: https://opencommons.uconn.edu/gs_theses/1123.

Council of Science Editors:

Yankee TN. Rank Aggregation of Feature Scoring Methods for Unsupervised Learning. [Masters Thesis]. University of Connecticut; 2017. Available from: https://opencommons.uconn.edu/gs_theses/1123


University of New South Wales

23. Xu, Jie. On-line and unsupervised learning for codebook based visual recognition.

Degree: Computer Science & Engineering, 2011, University of New South Wales

 In this thesis we develop unsupervised and on-line learning algorithmsfor codebook based visual recognition tasks. First, we study the Prob-abilistic Latent Semantic Analysis (PLSA), which… (more)

Subjects/Keywords: Visual recognition; Online learning; Unsupervised learning

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APA (6th Edition):

Xu, J. (2011). On-line and unsupervised learning for codebook based visual recognition. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51513 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10200/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Xu, Jie. “On-line and unsupervised learning for codebook based visual recognition.” 2011. Doctoral Dissertation, University of New South Wales. Accessed June 20, 2019. http://handle.unsw.edu.au/1959.4/51513 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10200/SOURCE02?view=true.

MLA Handbook (7th Edition):

Xu, Jie. “On-line and unsupervised learning for codebook based visual recognition.” 2011. Web. 20 Jun 2019.

Vancouver:

Xu J. On-line and unsupervised learning for codebook based visual recognition. [Internet] [Doctoral dissertation]. University of New South Wales; 2011. [cited 2019 Jun 20]. Available from: http://handle.unsw.edu.au/1959.4/51513 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10200/SOURCE02?view=true.

Council of Science Editors:

Xu J. On-line and unsupervised learning for codebook based visual recognition. [Doctoral Dissertation]. University of New South Wales; 2011. Available from: http://handle.unsw.edu.au/1959.4/51513 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10200/SOURCE02?view=true

24. Ebbesson, Magnus. Document Clustering.

Degree: 2010, Chalmers University of Technology

 Cluster analysis is a sub-field in artificial intelligence and machine learning that refers to a group of algorithms that try to find a natural grouping… (more)

Subjects/Keywords: document clustering; text clustering; cluster analysis; cluster; unsupervised categorisation

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APA (6th Edition):

Ebbesson, M. (2010). Document Clustering. (Thesis). Chalmers University of Technology. Retrieved from http://studentarbeten.chalmers.se/publication/128681-document-clustering

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):

Ebbesson, Magnus. “Document Clustering.” 2010. Thesis, Chalmers University of Technology. Accessed June 20, 2019. http://studentarbeten.chalmers.se/publication/128681-document-clustering.

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

MLA Handbook (7th Edition):

Ebbesson, Magnus. “Document Clustering.” 2010. Web. 20 Jun 2019.

Vancouver:

Ebbesson M. Document Clustering. [Internet] [Thesis]. Chalmers University of Technology; 2010. [cited 2019 Jun 20]. Available from: http://studentarbeten.chalmers.se/publication/128681-document-clustering.

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

Council of Science Editors:

Ebbesson M. Document Clustering. [Thesis]. Chalmers University of Technology; 2010. Available from: http://studentarbeten.chalmers.se/publication/128681-document-clustering

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


Linköping University

25. Alirezaie, Marjan. Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation.

Degree: Computer and Information Science, 2011, Linköping University

  The present thesis addresses machine learning in a domain of naturallanguage phrases that are names of universities. It describes two approaches to this problem… (more)

Subjects/Keywords: Machine Learning; Supervised Learning; Unsupervised Learning; Computer Sciences; Datavetenskap (datalogi)

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

APA (6th Edition):

Alirezaie, M. (2011). Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70086

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):

Alirezaie, Marjan. “Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation.” 2011. Thesis, Linköping University. Accessed June 20, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70086.

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

MLA Handbook (7th Edition):

Alirezaie, Marjan. “Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation.” 2011. Web. 20 Jun 2019.

Vancouver:

Alirezaie M. Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation. [Internet] [Thesis]. Linköping University; 2011. [cited 2019 Jun 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70086.

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

Council of Science Editors:

Alirezaie M. Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation. [Thesis]. Linköping University; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70086

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


KTH

26. Forstén, Andreas. Unsupervised Anomaly Detection in Receipt Data.

Degree: Computer Science and Communication (CSC), 2017, KTH

With the progress of data handling methods and computing power comes the possibility of automating tasks that are not necessarily handled by humans. This… (more)

Subjects/Keywords: Anomaly detection; receipt; unsupervised; Computer Sciences; Datavetenskap (datalogi)

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

APA (6th Edition):

Forstén, A. (2017). Unsupervised Anomaly Detection in Receipt Data. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215161

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):

Forstén, Andreas. “Unsupervised Anomaly Detection in Receipt Data.” 2017. Thesis, KTH. Accessed June 20, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215161.

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

MLA Handbook (7th Edition):

Forstén, Andreas. “Unsupervised Anomaly Detection in Receipt Data.” 2017. Web. 20 Jun 2019.

Vancouver:

Forstén A. Unsupervised Anomaly Detection in Receipt Data. [Internet] [Thesis]. KTH; 2017. [cited 2019 Jun 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215161.

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

Council of Science Editors:

Forstén A. Unsupervised Anomaly Detection in Receipt Data. [Thesis]. KTH; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215161

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


University of Western Australia

27. Colreavy, Erin Patricia. Unsupervised categorization : perceptual shift, strategy development, and general principles.

Degree: PhD, 2008, University of Western Australia

Unsupervised categorization is the task of classifying novel stimuli without external feedback or guidance, and is important for every day decisions such as deciding whether… (more)

Subjects/Keywords: Categorization (Psychology); Cognition; Perception; Unsupervised categorization; Supervised categorization

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

APA (6th Edition):

Colreavy, E. P. (2008). Unsupervised categorization : perceptual shift, strategy development, and general principles. (Doctoral Dissertation). University of Western Australia. Retrieved from http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=10612&local_base=GEN01-INS01

Chicago Manual of Style (16th Edition):

Colreavy, Erin Patricia. “Unsupervised categorization : perceptual shift, strategy development, and general principles.” 2008. Doctoral Dissertation, University of Western Australia. Accessed June 20, 2019. http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=10612&local_base=GEN01-INS01.

MLA Handbook (7th Edition):

Colreavy, Erin Patricia. “Unsupervised categorization : perceptual shift, strategy development, and general principles.” 2008. Web. 20 Jun 2019.

Vancouver:

Colreavy EP. Unsupervised categorization : perceptual shift, strategy development, and general principles. [Internet] [Doctoral dissertation]. University of Western Australia; 2008. [cited 2019 Jun 20]. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=10612&local_base=GEN01-INS01.

Council of Science Editors:

Colreavy EP. Unsupervised categorization : perceptual shift, strategy development, and general principles. [Doctoral Dissertation]. University of Western Australia; 2008. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=10612&local_base=GEN01-INS01


Georgia Tech

28. Liang, Yingyu. Modern aspects of unsupervised learning.

Degree: PhD, Computer Science, 2014, Georgia Tech

Unsupervised learning has become more and more important due to the recent explosion of data. Clustering, a key topic in unsupervised learning, is a well-studied… (more)

Subjects/Keywords: Unsupervised learning; Clustering; Perturbation resilience; Distributed clustering; Community detection

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

APA (6th Edition):

Liang, Y. (2014). Modern aspects of unsupervised learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52282

Chicago Manual of Style (16th Edition):

Liang, Yingyu. “Modern aspects of unsupervised learning.” 2014. Doctoral Dissertation, Georgia Tech. Accessed June 20, 2019. http://hdl.handle.net/1853/52282.

MLA Handbook (7th Edition):

Liang, Yingyu. “Modern aspects of unsupervised learning.” 2014. Web. 20 Jun 2019.

Vancouver:

Liang Y. Modern aspects of unsupervised learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/1853/52282.

Council of Science Editors:

Liang Y. Modern aspects of unsupervised learning. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52282


University of Plymouth

29. Tjhai, Gina C. Anomaly-based correlation of IDS alarms.

Degree: PhD, 2011, University of Plymouth

 An Intrusion Detection System (IDS) is one of the major techniques for securing information systems and keeping pace with current and potential threats and vulnerabilities… (more)

Subjects/Keywords: 621.382; Intrusion Detection System, False Alarms and Unsupervised- based Correlation

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

APA (6th Edition):

Tjhai, G. C. (2011). Anomaly-based correlation of IDS alarms. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/308

Chicago Manual of Style (16th Edition):

Tjhai, Gina C. “Anomaly-based correlation of IDS alarms.” 2011. Doctoral Dissertation, University of Plymouth. Accessed June 20, 2019. http://hdl.handle.net/10026.1/308.

MLA Handbook (7th Edition):

Tjhai, Gina C. “Anomaly-based correlation of IDS alarms.” 2011. Web. 20 Jun 2019.

Vancouver:

Tjhai GC. Anomaly-based correlation of IDS alarms. [Internet] [Doctoral dissertation]. University of Plymouth; 2011. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10026.1/308.

Council of Science Editors:

Tjhai GC. Anomaly-based correlation of IDS alarms. [Doctoral Dissertation]. University of Plymouth; 2011. Available from: http://hdl.handle.net/10026.1/308


University of Plymouth

30. Rumbell, Timothy. Self organisation and hierarchical concept representation in networks of spiking neurons.

Degree: PhD, 2013, University of Plymouth

 The aim of this work is to introduce modular processing mechanisms for cortical functions implemented in networks of spiking neurons. Neural maps are a feature… (more)

Subjects/Keywords: 573.8; Computational Neuroscience; Self Organising Maps; Spiking Neurons; Unsupervised Learning

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

APA (6th Edition):

Rumbell, T. (2013). Self organisation and hierarchical concept representation in networks of spiking neurons. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/1578

Chicago Manual of Style (16th Edition):

Rumbell, Timothy. “Self organisation and hierarchical concept representation in networks of spiking neurons.” 2013. Doctoral Dissertation, University of Plymouth. Accessed June 20, 2019. http://hdl.handle.net/10026.1/1578.

MLA Handbook (7th Edition):

Rumbell, Timothy. “Self organisation and hierarchical concept representation in networks of spiking neurons.” 2013. Web. 20 Jun 2019.

Vancouver:

Rumbell T. Self organisation and hierarchical concept representation in networks of spiking neurons. [Internet] [Doctoral dissertation]. University of Plymouth; 2013. [cited 2019 Jun 20]. Available from: http://hdl.handle.net/10026.1/1578.

Council of Science Editors:

Rumbell T. Self organisation and hierarchical concept representation in networks of spiking neurons. [Doctoral Dissertation]. University of Plymouth; 2013. Available from: http://hdl.handle.net/10026.1/1578

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