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You searched for subject:(Supervised learning). Showing records 1 – 30 of 891 total matches.

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1. Lease, Matthew A. Beyond keywords: finding information more accurately and easily using natural language.

Degree: PhD, Computer Science, 2009, Brown University

 Information retrieval (IR) has become a ubiquitous technology for quickly and easily finding information on a given topic amidst the wealth of digital content available… (more)

Subjects/Keywords: supervised learning

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APA (6th Edition):

Lease, M. A. (2009). Beyond keywords: finding information more accurately and easily using natural language. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:206/

Chicago Manual of Style (16th Edition):

Lease, Matthew A. “Beyond keywords: finding information more accurately and easily using natural language.” 2009. Doctoral Dissertation, Brown University. Accessed March 07, 2021. https://repository.library.brown.edu/studio/item/bdr:206/.

MLA Handbook (7th Edition):

Lease, Matthew A. “Beyond keywords: finding information more accurately and easily using natural language.” 2009. Web. 07 Mar 2021.

Vancouver:

Lease MA. Beyond keywords: finding information more accurately and easily using natural language. [Internet] [Doctoral dissertation]. Brown University; 2009. [cited 2021 Mar 07]. Available from: https://repository.library.brown.edu/studio/item/bdr:206/.

Council of Science Editors:

Lease MA. Beyond keywords: finding information more accurately and easily using natural language. [Doctoral Dissertation]. Brown University; 2009. Available from: https://repository.library.brown.edu/studio/item/bdr:206/


University of Illinois – Chicago

2. Mohammadi, Neshat. Supervised Tensor Learning with Applications.

Degree: 2017, University of Illinois – Chicago

 In this thesis, a new supervised tensor learning (STL) approach with application to neuroimages has been studied and implemented. We applied our proposed polynomial kernel-based… (more)

Subjects/Keywords: Supervised Tensor Learning

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APA (6th Edition):

Mohammadi, N. (2017). Supervised Tensor Learning with Applications. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22099

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):

Mohammadi, Neshat. “Supervised Tensor Learning with Applications.” 2017. Thesis, University of Illinois – Chicago. Accessed March 07, 2021. http://hdl.handle.net/10027/22099.

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

MLA Handbook (7th Edition):

Mohammadi, Neshat. “Supervised Tensor Learning with Applications.” 2017. Web. 07 Mar 2021.

Vancouver:

Mohammadi N. Supervised Tensor Learning with Applications. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10027/22099.

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

Council of Science Editors:

Mohammadi N. Supervised Tensor Learning with Applications. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/22099

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


Oregon State University

3. Hao, Guohua. Revisiting output coding for sequential supervised learning.

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

 Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training… (more)

Subjects/Keywords: ECOC; Supervised learning (Machine learning)

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APA (6th Edition):

Hao, G. (2009). Revisiting output coding for sequential supervised learning. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/10897

Chicago Manual of Style (16th Edition):

Hao, Guohua. “Revisiting output coding for sequential supervised learning.” 2009. Masters Thesis, Oregon State University. Accessed March 07, 2021. http://hdl.handle.net/1957/10897.

MLA Handbook (7th Edition):

Hao, Guohua. “Revisiting output coding for sequential supervised learning.” 2009. Web. 07 Mar 2021.

Vancouver:

Hao G. Revisiting output coding for sequential supervised learning. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1957/10897.

Council of Science Editors:

Hao G. Revisiting output coding for sequential supervised learning. [Masters Thesis]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/10897


Rutgers University

4. Gazzola, Gianluca. Supervised learning methods for variable importance and regression with uncertainty on dependent data.

Degree: PhD, Operations Research, 2019, Rutgers University

This dissertation covers a collection of supervised learning methods targeted to data with complex dependence patterns. Part of our work orbits around the concept of… (more)

Subjects/Keywords: Supervised learning (Machine learning)

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APA (6th Edition):

Gazzola, G. (2019). Supervised learning methods for variable importance and regression with uncertainty on dependent data. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/60158/

Chicago Manual of Style (16th Edition):

Gazzola, Gianluca. “Supervised learning methods for variable importance and regression with uncertainty on dependent data.” 2019. Doctoral Dissertation, Rutgers University. Accessed March 07, 2021. https://rucore.libraries.rutgers.edu/rutgers-lib/60158/.

MLA Handbook (7th Edition):

Gazzola, Gianluca. “Supervised learning methods for variable importance and regression with uncertainty on dependent data.” 2019. Web. 07 Mar 2021.

Vancouver:

Gazzola G. Supervised learning methods for variable importance and regression with uncertainty on dependent data. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2021 Mar 07]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60158/.

Council of Science Editors:

Gazzola G. Supervised learning methods for variable importance and regression with uncertainty on dependent data. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60158/

5. Aversano, Gianmarco. Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif.

Degree: Docteur es, Combustion, 2019, Université Paris-Saclay (ComUE); Université libre de Bruxelles (1970-....)

 L’objectif final étant de développer des modèles d’ordre réduit pour les applications de combustion, des techniques d’apprentissage automatique non supervisées et supervisées ont été testées… (more)

Subjects/Keywords: Combustion; Unsupervised learning; Supervised learning; Combustion; Unsupervised learning; Supervised learning

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APA (6th Edition):

Aversano, G. (2019). Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif. (Doctoral Dissertation). Université Paris-Saclay (ComUE); Université libre de Bruxelles (1970-....). Retrieved from http://www.theses.fr/2019SACLC095

Chicago Manual of Style (16th Edition):

Aversano, Gianmarco. “Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif.” 2019. Doctoral Dissertation, Université Paris-Saclay (ComUE); Université libre de Bruxelles (1970-....). Accessed March 07, 2021. http://www.theses.fr/2019SACLC095.

MLA Handbook (7th Edition):

Aversano, Gianmarco. “Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif.” 2019. Web. 07 Mar 2021.

Vancouver:

Aversano G. Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif. [Internet] [Doctoral dissertation]. Université Paris-Saclay (ComUE); Université libre de Bruxelles (1970-....); 2019. [cited 2021 Mar 07]. Available from: http://www.theses.fr/2019SACLC095.

Council of Science Editors:

Aversano G. Development of physics-based reduced-order models for reacting flow applications : Développement de modèles d’ordre réduit basés sur la physique pour les applications d’écoulement réactif. [Doctoral Dissertation]. Université Paris-Saclay (ComUE); Université libre de Bruxelles (1970-....); 2019. Available from: http://www.theses.fr/2019SACLC095


University of Adelaide

6. Shen, Tong. Context Learning and Weakly Supervised Learning for Semantic Segmentation.

Degree: 2018, University of Adelaide

 This thesis focuses on one of the fundamental problems in computer vision, semantic segmentation, whose task is to predict a semantic label for each pixel… (more)

Subjects/Keywords: weakly supervised learning; semantic segmentation

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

APA (6th Edition):

Shen, T. (2018). Context Learning and Weakly Supervised Learning for Semantic Segmentation. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/120354

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):

Shen, Tong. “Context Learning and Weakly Supervised Learning for Semantic Segmentation.” 2018. Thesis, University of Adelaide. Accessed March 07, 2021. http://hdl.handle.net/2440/120354.

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

MLA Handbook (7th Edition):

Shen, Tong. “Context Learning and Weakly Supervised Learning for Semantic Segmentation.” 2018. Web. 07 Mar 2021.

Vancouver:

Shen T. Context Learning and Weakly Supervised Learning for Semantic Segmentation. [Internet] [Thesis]. University of Adelaide; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/2440/120354.

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

Council of Science Editors:

Shen T. Context Learning and Weakly Supervised Learning for Semantic Segmentation. [Thesis]. University of Adelaide; 2018. Available from: http://hdl.handle.net/2440/120354

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


Delft University of Technology

7. Van Hecke, K.G. (author). Persistent self-supervised learning principle: Study and demonstration on flying robots.

Degree: 2015, Delft University of Technology

We introduce, study and demonstrate Persistent Self-Supervised Learning (PSSL), a machine learning method for usage onboard robotic platforms. The PSSL model leverages a standard supervised(more)

Subjects/Keywords: persistent self-supervised learning; MAV

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APA (6th Edition):

Van Hecke, K. G. (. (2015). Persistent self-supervised learning principle: Study and demonstration on flying robots. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b722da02-089f-42a8-a3ea-fb3f5900bcdd

Chicago Manual of Style (16th Edition):

Van Hecke, K G (author). “Persistent self-supervised learning principle: Study and demonstration on flying robots.” 2015. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:b722da02-089f-42a8-a3ea-fb3f5900bcdd.

MLA Handbook (7th Edition):

Van Hecke, K G (author). “Persistent self-supervised learning principle: Study and demonstration on flying robots.” 2015. Web. 07 Mar 2021.

Vancouver:

Van Hecke KG(. Persistent self-supervised learning principle: Study and demonstration on flying robots. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:b722da02-089f-42a8-a3ea-fb3f5900bcdd.

Council of Science Editors:

Van Hecke KG(. Persistent self-supervised learning principle: Study and demonstration on flying robots. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:b722da02-089f-42a8-a3ea-fb3f5900bcdd


Colorado School of Mines

8. Jackson, Ryan Blake. Machine learning for encrypted Amazon Echo traffic classification.

Degree: MS(M.S.), Computer Science, 2018, Colorado School of Mines

 As smart speakers like the Amazon Echo become more popular, they have given rise to rampant concerns regarding user privacy. This work investigates machine learning(more)

Subjects/Keywords: supervised classification; machine learning

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APA (6th Edition):

Jackson, R. B. (2018). Machine learning for encrypted Amazon Echo traffic classification. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172223

Chicago Manual of Style (16th Edition):

Jackson, Ryan Blake. “Machine learning for encrypted Amazon Echo traffic classification.” 2018. Masters Thesis, Colorado School of Mines. Accessed March 07, 2021. http://hdl.handle.net/11124/172223.

MLA Handbook (7th Edition):

Jackson, Ryan Blake. “Machine learning for encrypted Amazon Echo traffic classification.” 2018. Web. 07 Mar 2021.

Vancouver:

Jackson RB. Machine learning for encrypted Amazon Echo traffic classification. [Internet] [Masters thesis]. Colorado School of Mines; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11124/172223.

Council of Science Editors:

Jackson RB. Machine learning for encrypted Amazon Echo traffic classification. [Masters Thesis]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172223


Oklahoma State University

9. Spain, Marc. Study on log event noise reduction by using Naive Bayes supervised machine learning.

Degree: Computer Science, 2019, Oklahoma State University

 This research addresses which Naive Bayes model would be best to predict Windows log events that could be considered noise or in other words not… (more)

Subjects/Keywords: naive bayes; supervised machine learning

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APA (6th Edition):

Spain, M. (2019). Study on log event noise reduction by using Naive Bayes supervised machine learning. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/324912

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):

Spain, Marc. “Study on log event noise reduction by using Naive Bayes supervised machine learning.” 2019. Thesis, Oklahoma State University. Accessed March 07, 2021. http://hdl.handle.net/11244/324912.

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

MLA Handbook (7th Edition):

Spain, Marc. “Study on log event noise reduction by using Naive Bayes supervised machine learning.” 2019. Web. 07 Mar 2021.

Vancouver:

Spain M. Study on log event noise reduction by using Naive Bayes supervised machine learning. [Internet] [Thesis]. Oklahoma State University; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11244/324912.

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

Council of Science Editors:

Spain M. Study on log event noise reduction by using Naive Bayes supervised machine learning. [Thesis]. Oklahoma State University; 2019. Available from: http://hdl.handle.net/11244/324912

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


Wayne State University

10. Hailat, Zeyad. Deep Learning Methods For Visual Object Recognition.

Degree: PhD, Computer Science, 2018, Wayne State University

  Convolutional neural networks (CNNs) attain state-of-the-art performance on various classification tasks assuming a sufficiently large number of labeled training examples. Unfortunately, curating sufficiently large… (more)

Subjects/Keywords: artificial intelligence; deep learning; machine learning; self-learning; semi-supervised learning; supervised learning; Computer Sciences

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APA (6th Edition):

Hailat, Z. (2018). Deep Learning Methods For Visual Object Recognition. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/2026

Chicago Manual of Style (16th Edition):

Hailat, Zeyad. “Deep Learning Methods For Visual Object Recognition.” 2018. Doctoral Dissertation, Wayne State University. Accessed March 07, 2021. https://digitalcommons.wayne.edu/oa_dissertations/2026.

MLA Handbook (7th Edition):

Hailat, Zeyad. “Deep Learning Methods For Visual Object Recognition.” 2018. Web. 07 Mar 2021.

Vancouver:

Hailat Z. Deep Learning Methods For Visual Object Recognition. [Internet] [Doctoral dissertation]. Wayne State University; 2018. [cited 2021 Mar 07]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/2026.

Council of Science Editors:

Hailat Z. Deep Learning Methods For Visual Object Recognition. [Doctoral Dissertation]. Wayne State University; 2018. Available from: https://digitalcommons.wayne.edu/oa_dissertations/2026


University of Sydney

11. He, Fengxiang. Instance-Dependent Positive-Unlabelled Learning .

Degree: 2018, University of Sydney

 An emerging topic in machine learning is how to learn classifiers from datasets containing only positive and unlabelled examples (PU learning). This problem has significant… (more)

Subjects/Keywords: Postive-unlabelled learning; weakly supervised learning

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APA (6th Edition):

He, F. (2018). Instance-Dependent Positive-Unlabelled Learning . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/20115

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):

He, Fengxiang. “Instance-Dependent Positive-Unlabelled Learning .” 2018. Thesis, University of Sydney. Accessed March 07, 2021. http://hdl.handle.net/2123/20115.

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

MLA Handbook (7th Edition):

He, Fengxiang. “Instance-Dependent Positive-Unlabelled Learning .” 2018. Web. 07 Mar 2021.

Vancouver:

He F. Instance-Dependent Positive-Unlabelled Learning . [Internet] [Thesis]. University of Sydney; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/2123/20115.

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

Council of Science Editors:

He F. Instance-Dependent Positive-Unlabelled Learning . [Thesis]. University of Sydney; 2018. Available from: http://hdl.handle.net/2123/20115

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


University of Texas – Austin

12. Joshi, Shalmali Dilip. Constraint based approaches to interpretable and semi-supervised machine learning.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Texas – Austin

 Interpretability and Explainability of machine learning algorithms are becoming increasingly important as Machine Learning (ML) systems get widely applied to domains like clinical healthcare, social… (more)

Subjects/Keywords: Interpretable machine learning; Semi-supervised machine learning

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APA (6th Edition):

Joshi, S. D. (2019). Constraint based approaches to interpretable and semi-supervised machine learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/1259

Chicago Manual of Style (16th Edition):

Joshi, Shalmali Dilip. “Constraint based approaches to interpretable and semi-supervised machine learning.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 07, 2021. http://dx.doi.org/10.26153/tsw/1259.

MLA Handbook (7th Edition):

Joshi, Shalmali Dilip. “Constraint based approaches to interpretable and semi-supervised machine learning.” 2019. Web. 07 Mar 2021.

Vancouver:

Joshi SD. Constraint based approaches to interpretable and semi-supervised machine learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 07]. Available from: http://dx.doi.org/10.26153/tsw/1259.

Council of Science Editors:

Joshi SD. Constraint based approaches to interpretable and semi-supervised machine learning. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/1259

13. Byun, Byungki. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 This dissertation presents the development of a semi-supervised incremental learning framework with a multi-view perspective for image concept modeling. For reliable image concept characterization, having… (more)

Subjects/Keywords: Discriminative learning; Semi-supervised learning; Incremental learning; Image modeling; Multi-view learning; Machine learning; Supervised learning (Machine learning); Boosting (Algorithms)

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APA (6th Edition):

Byun, B. (2012). On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43597

Chicago Manual of Style (16th Edition):

Byun, Byungki. “On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.” 2012. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/43597.

MLA Handbook (7th Edition):

Byun, Byungki. “On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.” 2012. Web. 07 Mar 2021.

Vancouver:

Byun B. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/43597.

Council of Science Editors:

Byun B. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43597


University of Illinois – Urbana-Champaign

14. He, Shibi. Reinforced co-learning for semi-supervised ranking.

Degree: MS, Computer Science, 2018, University of Illinois – Urbana-Champaign

Learning to rank is vital to information retrieval and recommendation systems. Directly optimizing the listwise evaluation measure such as normalized discounted cumulative gain (NDCG) is… (more)

Subjects/Keywords: Learning to rank; Semi-supervised Learning; Reinforcement Learning; Machine Learning

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APA (6th Edition):

He, S. (2018). Reinforced co-learning for semi-supervised ranking. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/102868

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):

He, Shibi. “Reinforced co-learning for semi-supervised ranking.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed March 07, 2021. http://hdl.handle.net/2142/102868.

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

MLA Handbook (7th Edition):

He, Shibi. “Reinforced co-learning for semi-supervised ranking.” 2018. Web. 07 Mar 2021.

Vancouver:

He S. Reinforced co-learning for semi-supervised ranking. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/2142/102868.

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

Council of Science Editors:

He S. Reinforced co-learning for semi-supervised ranking. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/102868

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


University of Alberta

15. Mahmood, Ashique. Automatic step-size adaptation in incremental supervised learning.

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

 Performance and stability of many iterative algorithms such as stochastic gradient descent largely depend on a fixed and scalar step-size parameter. Use of a fixed… (more)

Subjects/Keywords: step size; supervised learning; stochastic gradient descent

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APA (6th Edition):

Mahmood, A. (2010). Automatic step-size adaptation in incremental supervised learning. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/zc77sr03r

Chicago Manual of Style (16th Edition):

Mahmood, Ashique. “Automatic step-size adaptation in incremental supervised learning.” 2010. Masters Thesis, University of Alberta. Accessed March 07, 2021. https://era.library.ualberta.ca/files/zc77sr03r.

MLA Handbook (7th Edition):

Mahmood, Ashique. “Automatic step-size adaptation in incremental supervised learning.” 2010. Web. 07 Mar 2021.

Vancouver:

Mahmood A. Automatic step-size adaptation in incremental supervised learning. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2021 Mar 07]. Available from: https://era.library.ualberta.ca/files/zc77sr03r.

Council of Science Editors:

Mahmood A. Automatic step-size adaptation in incremental supervised learning. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/zc77sr03r


Georgia Tech

16. Ahsan, Unaiza. Leveraging mid-level representations for complex activity recognition.

Degree: PhD, Interactive Computing, 2019, Georgia Tech

 Dynamic scene understanding requires learning representations of the components of the scene including objects, environments, actions and events. Complex activity recognition from images and videos… (more)

Subjects/Keywords: Activity recognition; Self-supervised learning; Event recognition

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

APA (6th Edition):

Ahsan, U. (2019). Leveraging mid-level representations for complex activity recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61199

Chicago Manual of Style (16th Edition):

Ahsan, Unaiza. “Leveraging mid-level representations for complex activity recognition.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/61199.

MLA Handbook (7th Edition):

Ahsan, Unaiza. “Leveraging mid-level representations for complex activity recognition.” 2019. Web. 07 Mar 2021.

Vancouver:

Ahsan U. Leveraging mid-level representations for complex activity recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/61199.

Council of Science Editors:

Ahsan U. Leveraging mid-level representations for complex activity recognition. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61199


McMaster University

17. Ateeq, Sameen. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.

Degree: MSc, 2018, McMaster University

According to the Public Health Agency of Canada, falls account for 95% of all hip fractures in Canada; 20% of fall-related injury cases end in… (more)

Subjects/Keywords: machine learning; supervised classification; falls; CCHS; injuries

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

APA (6th Edition):

Ateeq, S. (2018). Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/24095

Chicago Manual of Style (16th Edition):

Ateeq, Sameen. “Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.” 2018. Masters Thesis, McMaster University. Accessed March 07, 2021. http://hdl.handle.net/11375/24095.

MLA Handbook (7th Edition):

Ateeq, Sameen. “Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.” 2018. Web. 07 Mar 2021.

Vancouver:

Ateeq S. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. [Internet] [Masters thesis]. McMaster University; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11375/24095.

Council of Science Editors:

Ateeq S. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. [Masters Thesis]. McMaster University; 2018. Available from: http://hdl.handle.net/11375/24095


Baylor University

18. -1697-5430. Semi-supervised learning for electrocardiography signal classification.

Degree: M.S.E.C.E., Baylor University. Dept. of Electrical & Computer Engineering., 2018, Baylor University

 An electrocardiogram (ECG) is a cardiology test that provides information about the structure and function of the heart. The size of the ECG data collected… (more)

Subjects/Keywords: Semi-supervised learning; Electrocardiography; pattern recognition

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APA (6th Edition):

-1697-5430. (2018). Semi-supervised learning for electrocardiography signal classification. (Masters Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/10391

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

Chicago Manual of Style (16th Edition):

-1697-5430. “Semi-supervised learning for electrocardiography signal classification.” 2018. Masters Thesis, Baylor University. Accessed March 07, 2021. http://hdl.handle.net/2104/10391.

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

MLA Handbook (7th Edition):

-1697-5430. “Semi-supervised learning for electrocardiography signal classification.” 2018. Web. 07 Mar 2021.

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

Vancouver:

-1697-5430. Semi-supervised learning for electrocardiography signal classification. [Internet] [Masters thesis]. Baylor University; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/2104/10391.

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

Council of Science Editors:

-1697-5430. Semi-supervised learning for electrocardiography signal classification. [Masters Thesis]. Baylor University; 2018. Available from: http://hdl.handle.net/2104/10391

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


University of Manchester

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

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 March 07, 2021. 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. 07 Mar 2021.

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 2021 Mar 07]. 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

20. Zhao, Xuran. Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics.

Degree: Docteur es, Signal et images, 2013, Paris, ENST

Dans la plupart des systèmes biométriques de l’état de l’art, les données biométrique sont souvent représentés par des vecteurs de grande dimensionalité. La dimensionnalité d'éléments… (more)

Subjects/Keywords: Apprentissage semi-supervisé; Semi-supervised learning

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

APA (6th Edition):

Zhao, X. (2013). Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2013ENST0061

Chicago Manual of Style (16th Edition):

Zhao, Xuran. “Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics.” 2013. Doctoral Dissertation, Paris, ENST. Accessed March 07, 2021. http://www.theses.fr/2013ENST0061.

MLA Handbook (7th Edition):

Zhao, Xuran. “Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics.” 2013. Web. 07 Mar 2021.

Vancouver:

Zhao X. Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics. [Internet] [Doctoral dissertation]. Paris, ENST; 2013. [cited 2021 Mar 07]. Available from: http://www.theses.fr/2013ENST0061.

Council of Science Editors:

Zhao X. Réduction de la dimension multi-vue pour la biométrie multimodale : Multi-view dimensionality reduction for multi-modal biometrics. [Doctoral Dissertation]. Paris, ENST; 2013. Available from: http://www.theses.fr/2013ENST0061


Delft University of Technology

21. Paramkusam, Deepak (author). Comparison of Optimal Control Techniques for Learning-based RRT.

Degree: 2018, Delft University of Technology

 Kinodynamic motion planning for a robot involves generating a trajectory from a given robot state to goal state while satisfying kinematic and dynamic constraints. Rapidly-exploring… (more)

Subjects/Keywords: RRT; Supervised Learning; Optimal control; Motion Planning

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

APA (6th Edition):

Paramkusam, D. (. (2018). Comparison of Optimal Control Techniques for Learning-based RRT. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:742ed24e-0525-4ae2-b6d4-2dc6f69e60e1

Chicago Manual of Style (16th Edition):

Paramkusam, Deepak (author). “Comparison of Optimal Control Techniques for Learning-based RRT.” 2018. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:742ed24e-0525-4ae2-b6d4-2dc6f69e60e1.

MLA Handbook (7th Edition):

Paramkusam, Deepak (author). “Comparison of Optimal Control Techniques for Learning-based RRT.” 2018. Web. 07 Mar 2021.

Vancouver:

Paramkusam D(. Comparison of Optimal Control Techniques for Learning-based RRT. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:742ed24e-0525-4ae2-b6d4-2dc6f69e60e1.

Council of Science Editors:

Paramkusam D(. Comparison of Optimal Control Techniques for Learning-based RRT. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:742ed24e-0525-4ae2-b6d4-2dc6f69e60e1


Delft University of Technology

22. Moring, Stefan (author). Kinodynamic Steering using Supervised Learning in RRT.

Degree: 2018, Delft University of Technology

With the need for robots to operate autonomously increasing more and more, the research field of motion planning is becoming more active. Usually planning is… (more)

Subjects/Keywords: Motion Planning; RRT; Kinodynamic; Supervised Learning

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

APA (6th Edition):

Moring, S. (. (2018). Kinodynamic Steering using Supervised Learning in RRT. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:fdf13674-f2b5-4b4a-b03d-21299114642a

Chicago Manual of Style (16th Edition):

Moring, Stefan (author). “Kinodynamic Steering using Supervised Learning in RRT.” 2018. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:fdf13674-f2b5-4b4a-b03d-21299114642a.

MLA Handbook (7th Edition):

Moring, Stefan (author). “Kinodynamic Steering using Supervised Learning in RRT.” 2018. Web. 07 Mar 2021.

Vancouver:

Moring S(. Kinodynamic Steering using Supervised Learning in RRT. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:fdf13674-f2b5-4b4a-b03d-21299114642a.

Council of Science Editors:

Moring S(. Kinodynamic Steering using Supervised Learning in RRT. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:fdf13674-f2b5-4b4a-b03d-21299114642a


University of Victoria

23. Sharma, Mridula. Evaluating and enhancing the security of cyber physical systems using machine learning approaches.

Degree: Department of Electrical and Computer Engineering, 2020, University of Victoria

 The main aim of this dissertation is to address the security issues of the physical layer of Cyber Physical Systems. The network security is first… (more)

Subjects/Keywords: CPS; Supervised Machine Learning; RPL; Feature Selection

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

APA (6th Edition):

Sharma, M. (2020). Evaluating and enhancing the security of cyber physical systems using machine learning approaches. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/11675

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):

Sharma, Mridula. “Evaluating and enhancing the security of cyber physical systems using machine learning approaches.” 2020. Thesis, University of Victoria. Accessed March 07, 2021. http://hdl.handle.net/1828/11675.

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

MLA Handbook (7th Edition):

Sharma, Mridula. “Evaluating and enhancing the security of cyber physical systems using machine learning approaches.” 2020. Web. 07 Mar 2021.

Vancouver:

Sharma M. Evaluating and enhancing the security of cyber physical systems using machine learning approaches. [Internet] [Thesis]. University of Victoria; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1828/11675.

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

Council of Science Editors:

Sharma M. Evaluating and enhancing the security of cyber physical systems using machine learning approaches. [Thesis]. University of Victoria; 2020. Available from: http://hdl.handle.net/1828/11675

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


University of Notre Dame

24. Troy William Raeder. Evaluating and Maintaining Classification Algorithms</h1>.

Degree: Computer Science and Engineering, 2012, University of Notre Dame

  Any practical application of machine learning necessarily begins with the selection of a classification algorithm. Generally, practitioners will try several different types of algorithms… (more)

Subjects/Keywords: classification; supervised learning; evaluation; concept drift

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APA (6th Edition):

Raeder, T. W. (2012). Evaluating and Maintaining Classification Algorithms</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/4b29b56616h

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):

Raeder, Troy William. “Evaluating and Maintaining Classification Algorithms</h1>.” 2012. Thesis, University of Notre Dame. Accessed March 07, 2021. https://curate.nd.edu/show/4b29b56616h.

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

MLA Handbook (7th Edition):

Raeder, Troy William. “Evaluating and Maintaining Classification Algorithms</h1>.” 2012. Web. 07 Mar 2021.

Vancouver:

Raeder TW. Evaluating and Maintaining Classification Algorithms</h1>. [Internet] [Thesis]. University of Notre Dame; 2012. [cited 2021 Mar 07]. Available from: https://curate.nd.edu/show/4b29b56616h.

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

Council of Science Editors:

Raeder TW. Evaluating and Maintaining Classification Algorithms</h1>. [Thesis]. University of Notre Dame; 2012. Available from: https://curate.nd.edu/show/4b29b56616h

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


University of Tennessee – Knoxville

25. Amreen, Sadika. Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data.

Degree: 2019, University of Tennessee – Knoxville

 Operational data from software development, social networks and other domains are often contaminated with incorrect or missing values. Examples include misspelled or changed names, multiple… (more)

Subjects/Keywords: identity disambiguation; supervised learning; behavioral fingerprinting

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

APA (6th Edition):

Amreen, S. (2019). Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/5453

Chicago Manual of Style (16th Edition):

Amreen, Sadika. “Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data.” 2019. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed March 07, 2021. https://trace.tennessee.edu/utk_graddiss/5453.

MLA Handbook (7th Edition):

Amreen, Sadika. “Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data.” 2019. Web. 07 Mar 2021.

Vancouver:

Amreen S. Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2019. [cited 2021 Mar 07]. Available from: https://trace.tennessee.edu/utk_graddiss/5453.

Council of Science Editors:

Amreen S. Methods of Disambiguating and De-anonymizing Authorship in Large Scale Operational Data. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2019. Available from: https://trace.tennessee.edu/utk_graddiss/5453


University of North Texas

26. Dandala, Bharath. Multilingual Word Sense Disambiguation Using Wikipedia.

Degree: 2013, University of North Texas

 Ambiguity is inherent to human language. In particular, word sense ambiguity is prevalent in all natural languages, with a large number of the words in… (more)

Subjects/Keywords: Wikipedia; word sense disambiguation; supervised learning; multilingual

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

APA (6th Edition):

Dandala, B. (2013). Multilingual Word Sense Disambiguation Using Wikipedia. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc500036/

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):

Dandala, Bharath. “Multilingual Word Sense Disambiguation Using Wikipedia.” 2013. Thesis, University of North Texas. Accessed March 07, 2021. https://digital.library.unt.edu/ark:/67531/metadc500036/.

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

MLA Handbook (7th Edition):

Dandala, Bharath. “Multilingual Word Sense Disambiguation Using Wikipedia.” 2013. Web. 07 Mar 2021.

Vancouver:

Dandala B. Multilingual Word Sense Disambiguation Using Wikipedia. [Internet] [Thesis]. University of North Texas; 2013. [cited 2021 Mar 07]. Available from: https://digital.library.unt.edu/ark:/67531/metadc500036/.

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

Council of Science Editors:

Dandala B. Multilingual Word Sense Disambiguation Using Wikipedia. [Thesis]. University of North Texas; 2013. Available from: https://digital.library.unt.edu/ark:/67531/metadc500036/

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


Penn State University

27. Biyani, Prakhar. Analyzing Subjectivity and Sentiment of Online Forums.

Degree: 2014, Penn State University

 Online social media has emerged as a popular medium for seeking and providing information, opinions and social support. Online sites such as discussion forums, blogs… (more)

Subjects/Keywords: Subjectivity analysis; sentiment analysis; classification; supervised learning; semi-supervised learning; online forums

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

APA (6th Edition):

Biyani, P. (2014). Analyzing Subjectivity and Sentiment of Online Forums. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/22850

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):

Biyani, Prakhar. “Analyzing Subjectivity and Sentiment of Online Forums.” 2014. Thesis, Penn State University. Accessed March 07, 2021. https://submit-etda.libraries.psu.edu/catalog/22850.

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

MLA Handbook (7th Edition):

Biyani, Prakhar. “Analyzing Subjectivity and Sentiment of Online Forums.” 2014. Web. 07 Mar 2021.

Vancouver:

Biyani P. Analyzing Subjectivity and Sentiment of Online Forums. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Mar 07]. Available from: https://submit-etda.libraries.psu.edu/catalog/22850.

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

Council of Science Editors:

Biyani P. Analyzing Subjectivity and Sentiment of Online Forums. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/22850

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


Oregon State University

28. Hao, Guohua. Efficient training and feature induction in sequential supervised learning.

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

 Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature… (more)

Subjects/Keywords: Machine Learning; Supervised learning (Machine learning)  – Mathematical models

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

APA (6th Edition):

Hao, G. (2009). Efficient training and feature induction in sequential supervised learning. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/12548

Chicago Manual of Style (16th Edition):

Hao, Guohua. “Efficient training and feature induction in sequential supervised learning.” 2009. Doctoral Dissertation, Oregon State University. Accessed March 07, 2021. http://hdl.handle.net/1957/12548.

MLA Handbook (7th Edition):

Hao, Guohua. “Efficient training and feature induction in sequential supervised learning.” 2009. Web. 07 Mar 2021.

Vancouver:

Hao G. Efficient training and feature induction in sequential supervised learning. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1957/12548.

Council of Science Editors:

Hao G. Efficient training and feature induction in sequential supervised learning. [Doctoral Dissertation]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/12548


Linköping University

29. 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 March 07, 2021. 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. 07 Mar 2021.

Vancouver:

Alirezaie M. Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation. [Internet] [Thesis]. Linköping University; 2011. [cited 2021 Mar 07]. 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


Delft University of Technology

30. Jurasiński, Karol (author). Towards deeper understanding of semi-supervised learning with variational autoencoders.

Degree: 2019, Delft University of Technology

 Recently, deep generative models have been shown to achieve state-of-the-art performance on semi-supervised learning tasks. In particular, variational autoencoders have been adopted to use labeled… (more)

Subjects/Keywords: semi-supervised learning; variational inference; deep learning; machine learning

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

APA (6th Edition):

Jurasiński, K. (. (2019). Towards deeper understanding of semi-supervised learning with variational autoencoders. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb

Chicago Manual of Style (16th Edition):

Jurasiński, Karol (author). “Towards deeper understanding of semi-supervised learning with variational autoencoders.” 2019. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb.

MLA Handbook (7th Edition):

Jurasiński, Karol (author). “Towards deeper understanding of semi-supervised learning with variational autoencoders.” 2019. Web. 07 Mar 2021.

Vancouver:

Jurasiński K(. Towards deeper understanding of semi-supervised learning with variational autoencoders. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb.

Council of Science Editors:

Jurasiński K(. Towards deeper understanding of semi-supervised learning with variational autoencoders. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb

[1] [2] [3] [4] [5] … [30]

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