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You searched for subject:( Machine Learning). Showing records 1 – 30 of 7825 total matches.

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Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Masters Thesis, Oregon State University. Accessed November 20, 2019. http://hdl.handle.net/1957/10191.

MLA Handbook (7th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Web. 20 Nov 2019.

Vancouver:

Vatturi PK. Rare category detection using hierarchical mean shift. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/1957/10191.

Council of Science Editors:

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


Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Doctoral Dissertation, Oregon State University. Accessed November 20, 2019. http://hdl.handle.net/1957/12549.

MLA Handbook (7th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Web. 20 Nov 2019.

Vancouver:

Bao X. Applying machine learning for prediction, recommendation, and integration. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/1957/12549.

Council of Science Editors:

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


Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Doctoral Dissertation, Oregon State University. Accessed November 20, 2019. http://hdl.handle.net/1957/59159.

MLA Handbook (7th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Web. 20 Nov 2019.

Vancouver:

Liu L. Machine Learning Methods for Computational Sustainability. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/1957/59159.

Council of Science Editors:

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


Oregon State University

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

Degree: MS, Geography, 2017, Oregon State University

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Hooper, Samuel. “Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.” 2017. Masters Thesis, Oregon State University. Accessed November 20, 2019. http://hdl.handle.net/1957/60148.

MLA Handbook (7th Edition):

Hooper, Samuel. “Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.” 2017. Web. 20 Nov 2019.

Vancouver:

Hooper S. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. [Internet] [Masters thesis]. Oregon State University; 2017. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/1957/60148.

Council of Science Editors:

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


University of Georgia

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

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

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

U, Man Chon. “Improving learning outcomes by using clustering validity analysis to reduce label uncertainty.” 2013. Doctoral Dissertation, University of Georgia. Accessed November 20, 2019. http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd.

MLA Handbook (7th Edition):

U, Man Chon. “Improving learning outcomes by using clustering validity analysis to reduce label uncertainty.” 2013. Web. 20 Nov 2019.

Vancouver:

U MC. Improving learning outcomes by using clustering validity analysis to reduce label uncertainty. [Internet] [Doctoral dissertation]. University of Georgia; 2013. [cited 2019 Nov 20]. Available from: http://purl.galileo.usg.edu/uga_etd/u_man-chon_201308_phd.

Council of Science Editors:

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


University of Georgia

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

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

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

Subjects/Keywords: machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Richardson, William Dale. “Evolutionary instance resampling for difficult data sets.” 2013. Masters Thesis, University of Georgia. Accessed November 20, 2019. http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms.

MLA Handbook (7th Edition):

Richardson, William Dale. “Evolutionary instance resampling for difficult data sets.” 2013. Web. 20 Nov 2019.

Vancouver:

Richardson WD. Evolutionary instance resampling for difficult data sets. [Internet] [Masters thesis]. University of Georgia; 2013. [cited 2019 Nov 20]. Available from: http://purl.galileo.usg.edu/uga_etd/richardson_william_d_201312_ms.

Council of Science Editors:

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


University of Georgia

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

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

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Lyle, Arlo. “Baseball prediction using ensemble learning.” 2007. Masters Thesis, University of Georgia. Accessed November 20, 2019. http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms.

MLA Handbook (7th Edition):

Lyle, Arlo. “Baseball prediction using ensemble learning.” 2007. Web. 20 Nov 2019.

Vancouver:

Lyle A. Baseball prediction using ensemble learning. [Internet] [Masters thesis]. University of Georgia; 2007. [cited 2019 Nov 20]. Available from: http://purl.galileo.usg.edu/uga_etd/lyle_arlo_m_200705_ms.

Council of Science Editors:

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


Penn State University

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

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

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Gowda Aghalya Shyama Sundar, Deepika. “Identifying Product Web Pages Using Support Vector Machines.” 2010. Masters Thesis, Penn State University. Accessed November 20, 2019. https://etda.libraries.psu.edu/catalog/10299.

MLA Handbook (7th Edition):

Gowda Aghalya Shyama Sundar, Deepika. “Identifying Product Web Pages Using Support Vector Machines.” 2010. Web. 20 Nov 2019.

Vancouver:

Gowda Aghalya Shyama Sundar D. Identifying Product Web Pages Using Support Vector Machines. [Internet] [Masters thesis]. Penn State University; 2010. [cited 2019 Nov 20]. Available from: https://etda.libraries.psu.edu/catalog/10299.

Council of Science Editors:

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


University of California – San Diego

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

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

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

Subjects/Keywords: Machine learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Gallagher, Patrick W. “Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.” 2014. Thesis, University of California – San Diego. Accessed November 20, 2019. http://www.escholarship.org/uc/item/153375qt.

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

MLA Handbook (7th Edition):

Gallagher, Patrick W. “Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.” 2014. Web. 20 Nov 2019.

Vancouver:

Gallagher PW. Operator Theory for Analysis of Convex Optimization Methods in Machine Learning. [Internet] [Thesis]. University of California – San Diego; 2014. [cited 2019 Nov 20]. Available from: http://www.escholarship.org/uc/item/153375qt.

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

Council of Science Editors:

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

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


University of Victoria

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

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

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

Subjects/Keywords: Machine learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Lam, Newman Ming Ki. “Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies.” 2018. Thesis, University of Victoria. Accessed November 20, 2019. https://dspace.library.uvic.ca//handle/1828/9498.

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

MLA Handbook (7th Edition):

Lam, Newman Ming Ki. “Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies.” 2018. Web. 20 Nov 2019.

Vancouver:

Lam NMK. Learning in the real world environment: a classification model based on sensitivity to within-dimension and between-category variation of feature frequencies. [Internet] [Thesis]. University of Victoria; 2018. [cited 2019 Nov 20]. Available from: https://dspace.library.uvic.ca//handle/1828/9498.

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

Council of Science Editors:

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

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


University of Oxford

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

Degree: PhD, 2017, University of Oxford

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Bouchacourt, Diane. “Task-oriented learning of structured probability distributions.” 2017. Doctoral Dissertation, University of Oxford. Accessed November 20, 2019. https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819.

MLA Handbook (7th Edition):

Bouchacourt, Diane. “Task-oriented learning of structured probability distributions.” 2017. Web. 20 Nov 2019.

Vancouver:

Bouchacourt D. Task-oriented learning of structured probability distributions. [Internet] [Doctoral dissertation]. University of Oxford; 2017. [cited 2019 Nov 20]. Available from: https://ora.ox.ac.uk/objects/uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740819.

Council of Science Editors:

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


Oregon State University

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

Degree: PhD, 2017, Oregon State University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Doctoral Dissertation, Oregon State University. Accessed November 20, 2019. http://hdl.handle.net/1957/61580.

MLA Handbook (7th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Web. 20 Nov 2019.

Vancouver:

Das S. Incorporating User Feedback into Machine Learning Systems. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/1957/61580.

Council of Science Editors:

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


University of Waikato

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

Degree: 2011, University of Waikato

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Han, Zhimeng. “Smoothing in Probability Estimation Trees .” 2011. Masters Thesis, University of Waikato. Accessed November 20, 2019. http://hdl.handle.net/10289/5701.

MLA Handbook (7th Edition):

Han, Zhimeng. “Smoothing in Probability Estimation Trees .” 2011. Web. 20 Nov 2019.

Vancouver:

Han Z. Smoothing in Probability Estimation Trees . [Internet] [Masters thesis]. University of Waikato; 2011. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/10289/5701.

Council of Science Editors:

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


University of North Carolina – Greensboro

14. Al-Hamadani, Mokhaled N.A. Evaluation of the performance of deep learning techniques over tampered dataset.

Degree: 2015, University of North Carolina – Greensboro

 The reduction of classification error over supervised data sets is the main goal in Deep Learning (DL) approaches. However, tampered data is a serious problem… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Al-Hamadani, M. N. A. (2015). Evaluation of the performance of deep learning techniques over tampered dataset. (Masters Thesis). University of North Carolina – Greensboro. Retrieved from http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18053

Chicago Manual of Style (16th Edition):

Al-Hamadani, Mokhaled N A. “Evaluation of the performance of deep learning techniques over tampered dataset.” 2015. Masters Thesis, University of North Carolina – Greensboro. Accessed November 20, 2019. http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18053.

MLA Handbook (7th Edition):

Al-Hamadani, Mokhaled N A. “Evaluation of the performance of deep learning techniques over tampered dataset.” 2015. Web. 20 Nov 2019.

Vancouver:

Al-Hamadani MNA. Evaluation of the performance of deep learning techniques over tampered dataset. [Internet] [Masters thesis]. University of North Carolina – Greensboro; 2015. [cited 2019 Nov 20]. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18053.

Council of Science Editors:

Al-Hamadani MNA. Evaluation of the performance of deep learning techniques over tampered dataset. [Masters Thesis]. University of North Carolina – Greensboro; 2015. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18053


Wake Forest University

15. Patel, Udita. Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture.

Degree: 2016, Wake Forest University

 The quantity of electronic data available for analysis has grown exponentially with the rapid development of the World Wide Web, the Internet of Things, and… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Patel, U. (2016). Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture. (Thesis). Wake Forest University. Retrieved from http://hdl.handle.net/10339/59315

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):

Patel, Udita. “Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture.” 2016. Thesis, Wake Forest University. Accessed November 20, 2019. http://hdl.handle.net/10339/59315.

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

MLA Handbook (7th Edition):

Patel, Udita. “Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture.” 2016. Web. 20 Nov 2019.

Vancouver:

Patel U. Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture. [Internet] [Thesis]. Wake Forest University; 2016. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/10339/59315.

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

Council of Science Editors:

Patel U. Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture. [Thesis]. Wake Forest University; 2016. Available from: http://hdl.handle.net/10339/59315

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


University of Illinois – Urbana-Champaign

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

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

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Cai, Deng. “Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning.” 2009. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed November 20, 2019. http://hdl.handle.net/2142/11702.

MLA Handbook (7th Edition):

Cai, Deng. “Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning.” 2009. Web. 20 Nov 2019.

Vancouver:

Cai D. Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2009. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/2142/11702.

Council of Science Editors:

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


University of Illinois – Urbana-Champaign

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

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

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Jiang, Yiming. “Improvements and augmentations to Learning Based Java: a Java based learning based programming language.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed November 20, 2019. http://hdl.handle.net/2142/90827.

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

MLA Handbook (7th Edition):

Jiang, Yiming. “Improvements and augmentations to Learning Based Java: a Java based learning based programming language.” 2016. Web. 20 Nov 2019.

Vancouver:

Jiang Y. Improvements and augmentations to Learning Based Java: a Java based learning based programming language. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/2142/90827.

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

Council of Science Editors:

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

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


California State Polytechnic University – Pomona

18. Alarifi, Hana. Using Machine Learning to Predict Autism: Multiple Algorithms Comparison.

Degree: MS, Department of Computer Science, 2018, California State Polytechnic University – Pomona

Machine learning is one of the most important current technologies. In many aspects of research, machine learning played an extensive role for development especially in… (more)

Subjects/Keywords: machine learning

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

APA (6th Edition):

Alarifi, H. (2018). Using Machine Learning to Predict Autism: Multiple Algorithms Comparison. (Masters Thesis). California State Polytechnic University – Pomona. Retrieved from http://hdl.handle.net/10211.3/206664

Chicago Manual of Style (16th Edition):

Alarifi, Hana. “Using Machine Learning to Predict Autism: Multiple Algorithms Comparison.” 2018. Masters Thesis, California State Polytechnic University – Pomona. Accessed November 20, 2019. http://hdl.handle.net/10211.3/206664.

MLA Handbook (7th Edition):

Alarifi, Hana. “Using Machine Learning to Predict Autism: Multiple Algorithms Comparison.” 2018. Web. 20 Nov 2019.

Vancouver:

Alarifi H. Using Machine Learning to Predict Autism: Multiple Algorithms Comparison. [Internet] [Masters thesis]. California State Polytechnic University – Pomona; 2018. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/10211.3/206664.

Council of Science Editors:

Alarifi H. Using Machine Learning to Predict Autism: Multiple Algorithms Comparison. [Masters Thesis]. California State Polytechnic University – Pomona; 2018. Available from: http://hdl.handle.net/10211.3/206664


California State Polytechnic University – Pomona

19. Li, Wie Hsing. Detecting Non-Credible News Using Machine Learning.

Degree: MS, Department of Computer Science, 2018, California State Polytechnic University – Pomona

 Many of us are connected to various social media outlets such as Facebook and Twitter. Social media is an online place where one could share… (more)

Subjects/Keywords: machine learning

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

APA (6th Edition):

Li, W. H. (2018). Detecting Non-Credible News Using Machine Learning. (Masters Thesis). California State Polytechnic University – Pomona. Retrieved from http://hdl.handle.net/10211.3/206666

Chicago Manual of Style (16th Edition):

Li, Wie Hsing. “Detecting Non-Credible News Using Machine Learning.” 2018. Masters Thesis, California State Polytechnic University – Pomona. Accessed November 20, 2019. http://hdl.handle.net/10211.3/206666.

MLA Handbook (7th Edition):

Li, Wie Hsing. “Detecting Non-Credible News Using Machine Learning.” 2018. Web. 20 Nov 2019.

Vancouver:

Li WH. Detecting Non-Credible News Using Machine Learning. [Internet] [Masters thesis]. California State Polytechnic University – Pomona; 2018. [cited 2019 Nov 20]. Available from: http://hdl.handle.net/10211.3/206666.

Council of Science Editors:

Li WH. Detecting Non-Credible News Using Machine Learning. [Masters Thesis]. California State Polytechnic University – Pomona; 2018. Available from: http://hdl.handle.net/10211.3/206666

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

Degree: School of Engineering, 2018, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Khorshidi, Alireza. “Methods and Theories in Atomistic Reaction Engineering.” 2018. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792658/.

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

MLA Handbook (7th Edition):

Khorshidi, Alireza. “Methods and Theories in Atomistic Reaction Engineering.” 2018. Web. 20 Nov 2019.

Vancouver:

Khorshidi A. Methods and Theories in Atomistic Reaction Engineering. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792658/.

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

Council of Science Editors:

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

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

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

Degree: Department of Applied Mathematics, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Lee, Seungjoon. “Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.” 2017. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:733405/.

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

MLA Handbook (7th Edition):

Lee, Seungjoon. “Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.” 2017. Web. 20 Nov 2019.

Vancouver:

Lee S. Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:733405/.

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

Council of Science Editors:

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

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

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

Degree: Department of Computer Science, 2018, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Brawner, Stephen Andrew. “Algorithms for the Personalization of AI for Robots and the Smart Home.” 2018. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792905/.

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

MLA Handbook (7th Edition):

Brawner, Stephen Andrew. “Algorithms for the Personalization of AI for Robots and the Smart Home.” 2018. Web. 20 Nov 2019.

Vancouver:

Brawner SA. Algorithms for the Personalization of AI for Robots and the Smart Home. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792905/.

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

Council of Science Editors:

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

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

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

Degree: Biomedical Engineering, 2018, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Wang, Yinong. “Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.” 2018. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792720/.

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

MLA Handbook (7th Edition):

Wang, Yinong. “Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.” 2018. Web. 20 Nov 2019.

Vancouver:

Wang Y. Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792720/.

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

Council of Science Editors:

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

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

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

Degree: School of Engineering, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Patil, Prerna. “Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.” 2017. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:733471/.

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

MLA Handbook (7th Edition):

Patil, Prerna. “Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.” 2017. Web. 20 Nov 2019.

Vancouver:

Patil P. Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:733471/.

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

Council of Science Editors:

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

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

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

Degree: Department of Applied Mathematics, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:733424/.

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

MLA Handbook (7th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Web. 20 Nov 2019.

Vancouver:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:733424/.

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

Council of Science Editors:

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

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

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

Degree: Department of Computer Science, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792615/.

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

MLA Handbook (7th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Web. 20 Nov 2019.

Vancouver:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792615/.

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

Council of Science Editors:

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

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

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

Degree: Department of Computer Science, 2018, Brown University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792891/.

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

MLA Handbook (7th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Web. 20 Nov 2019.

Vancouver:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792891/.

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

Council of Science Editors:

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

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

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

Degree: Department of Applied Mathematics, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Tang, Yu-Hang. “Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.” 2017. Thesis, Brown University. Accessed November 20, 2019. https://repository.library.brown.edu/studio/item/bdr:792611/.

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

MLA Handbook (7th Edition):

Tang, Yu-Hang. “Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.” 2017. Web. 20 Nov 2019.

Vancouver:

Tang Y. Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 20]. Available from: https://repository.library.brown.edu/studio/item/bdr:792611/.

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

Council of Science Editors:

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

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

29. Masci, Jonathan. Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions.

Degree: 2014, Università della Svizzera italiana

Learning features for object detection and recognition with deep learning has received increasing attention in the past several years and recently attained widespread popularity. In… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Masci, J. (2014). Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/210177

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):

Masci, Jonathan. “Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions.” 2014. Thesis, Università della Svizzera italiana. Accessed November 20, 2019. http://doc.rero.ch/record/210177.

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

MLA Handbook (7th Edition):

Masci, Jonathan. “Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions.” 2014. Web. 20 Nov 2019.

Vancouver:

Masci J. Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions. [Internet] [Thesis]. Università della Svizzera italiana; 2014. [cited 2019 Nov 20]. Available from: http://doc.rero.ch/record/210177.

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

Council of Science Editors:

Masci J. Advances in deep learning for vision, with applications to industrial inspection: classification, segmentation and morphological extensions. [Thesis]. Università della Svizzera italiana; 2014. Available from: http://doc.rero.ch/record/210177

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


Università della Svizzera italiana

30. Bacchelli, Alberto. Mining unstructured software data.

Degree: 2013, Università della Svizzera italiana

 Our thesis is that the analysis of unstructured data supports software understanding and evolution analysis, and complements the data mined from structured sources. To this… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Bacchelli, A. (2013). Mining unstructured software data. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/203066

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):

Bacchelli, Alberto. “Mining unstructured software data.” 2013. Thesis, Università della Svizzera italiana. Accessed November 20, 2019. http://doc.rero.ch/record/203066.

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

MLA Handbook (7th Edition):

Bacchelli, Alberto. “Mining unstructured software data.” 2013. Web. 20 Nov 2019.

Vancouver:

Bacchelli A. Mining unstructured software data. [Internet] [Thesis]. Università della Svizzera italiana; 2013. [cited 2019 Nov 20]. Available from: http://doc.rero.ch/record/203066.

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

Council of Science Editors:

Bacchelli A. Mining unstructured software data. [Thesis]. Università della Svizzera italiana; 2013. Available from: http://doc.rero.ch/record/203066

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

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