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You searched for subject:(Machine learning ). Showing records 1 – 30 of 10102 total matches.

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Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Doctoral Dissertation, Oregon State University. Accessed September 18, 2020. http://hdl.handle.net/1957/59159.

MLA Handbook (7th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Web. 18 Sep 2020.

Vancouver:

Liu L. Machine Learning Methods for Computational Sustainability. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/1957/59159.

Council of Science Editors:

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


Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Masters Thesis, Oregon State University. Accessed September 18, 2020. http://hdl.handle.net/1957/10191.

MLA Handbook (7th Edition):

Vatturi, Pavan Kumar. “Rare category detection using hierarchical mean shift.” 2009. Web. 18 Sep 2020.

Vancouver:

Vatturi PK. Rare category detection using hierarchical mean shift. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/1957/10191.

Council of Science Editors:

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


Oregon State University

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

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

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

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Doctoral Dissertation, Oregon State University. Accessed September 18, 2020. http://hdl.handle.net/1957/12549.

MLA Handbook (7th Edition):

Bao, Xinlong. “Applying machine learning for prediction, recommendation, and integration.” 2009. Web. 18 Sep 2020.

Vancouver:

Bao X. Applying machine learning for prediction, recommendation, and integration. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2020 Sep 18]. 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

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 September 18, 2020. http://hdl.handle.net/1957/60148.

MLA Handbook (7th Edition):

Hooper, Samuel. “Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale.” 2017. Web. 18 Sep 2020.

Vancouver:

Hooper S. Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale. [Internet] [Masters thesis]. Oregon State University; 2017. [cited 2020 Sep 18]. 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


Texas A&M University

5. Kapale, Anurag. An Automated Framework To Generate End-to-End Machine Learning Pipelines.

Degree: MS, Computer Science, 2019, Texas A&M University

 The recent developments in machine learning have shown its applicability in numerous real-world applications. However, building an optimal machine learning pipeline requires considerable knowledge and… (more)

Subjects/Keywords: Machine Learning; Automated Machine Learning

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APA (6th Edition):

Kapale, A. (2019). An Automated Framework To Generate End-to-End Machine Learning Pipelines. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/188756

Chicago Manual of Style (16th Edition):

Kapale, Anurag. “An Automated Framework To Generate End-to-End Machine Learning Pipelines.” 2019. Masters Thesis, Texas A&M University. Accessed September 18, 2020. http://hdl.handle.net/1969.1/188756.

MLA Handbook (7th Edition):

Kapale, Anurag. “An Automated Framework To Generate End-to-End Machine Learning Pipelines.” 2019. Web. 18 Sep 2020.

Vancouver:

Kapale A. An Automated Framework To Generate End-to-End Machine Learning Pipelines. [Internet] [Masters thesis]. Texas A&M University; 2019. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/1969.1/188756.

Council of Science Editors:

Kapale A. An Automated Framework To Generate End-to-End Machine Learning Pipelines. [Masters Thesis]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/188756


Rutgers University

6. Imtiaz, Hafiz, 1986-. Decentralized differentially private algorithms for matrix and tensor factorization.

Degree: PhD, Electrical and Computer Engineering, 2020, Rutgers University

Many applications of machine learning, such as human health research, involve processing private or sensitive information. Privacy concerns may impose significant hurdles to collaboration in… (more)

Subjects/Keywords: Decentralized machine learning; Machine learning

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APA (6th Edition):

Imtiaz, Hafiz, 1. (2020). Decentralized differentially private algorithms for matrix and tensor factorization. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/62938/

Chicago Manual of Style (16th Edition):

Imtiaz, Hafiz, 1986-. “Decentralized differentially private algorithms for matrix and tensor factorization.” 2020. Doctoral Dissertation, Rutgers University. Accessed September 18, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/62938/.

MLA Handbook (7th Edition):

Imtiaz, Hafiz, 1986-. “Decentralized differentially private algorithms for matrix and tensor factorization.” 2020. Web. 18 Sep 2020.

Vancouver:

Imtiaz, Hafiz 1. Decentralized differentially private algorithms for matrix and tensor factorization. [Internet] [Doctoral dissertation]. Rutgers University; 2020. [cited 2020 Sep 18]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62938/.

Council of Science Editors:

Imtiaz, Hafiz 1. Decentralized differentially private algorithms for matrix and tensor factorization. [Doctoral Dissertation]. Rutgers University; 2020. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62938/


University of California – San Diego

7. 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 September 18, 2020. http://www.escholarship.org/uc/item/153375qt.

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

MLA Handbook (7th Edition):

Gallagher, Patrick W. “Operator Theory for Analysis of Convex Optimization Methods in Machine Learning.” 2014. Web. 18 Sep 2020.

Vancouver:

Gallagher PW. Operator Theory for Analysis of Convex Optimization Methods in Machine Learning. [Internet] [Thesis]. University of California – San Diego; 2014. [cited 2020 Sep 18]. 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 Oxford

8. Cobb, Adam Derek. The practicalities of scaling Bayesian neural networks to real-world applications.

Degree: PhD, 2020, University of Oxford

 In this work, I will focus on ways in which we can build machine learning models that appropriately account for uncertainty, whether with computationally cheap… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Cobb, A. D. (2020). The practicalities of scaling Bayesian neural networks to real-world applications. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:4b738b70-28bc-4545-86a6-6078861e7d13 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800130

Chicago Manual of Style (16th Edition):

Cobb, Adam Derek. “The practicalities of scaling Bayesian neural networks to real-world applications.” 2020. Doctoral Dissertation, University of Oxford. Accessed September 18, 2020. http://ora.ox.ac.uk/objects/uuid:4b738b70-28bc-4545-86a6-6078861e7d13 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800130.

MLA Handbook (7th Edition):

Cobb, Adam Derek. “The practicalities of scaling Bayesian neural networks to real-world applications.” 2020. Web. 18 Sep 2020.

Vancouver:

Cobb AD. The practicalities of scaling Bayesian neural networks to real-world applications. [Internet] [Doctoral dissertation]. University of Oxford; 2020. [cited 2020 Sep 18]. Available from: http://ora.ox.ac.uk/objects/uuid:4b738b70-28bc-4545-86a6-6078861e7d13 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800130.

Council of Science Editors:

Cobb AD. The practicalities of scaling Bayesian neural networks to real-world applications. [Doctoral Dissertation]. University of Oxford; 2020. Available from: http://ora.ox.ac.uk/objects/uuid:4b738b70-28bc-4545-86a6-6078861e7d13 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800130


University of Oxford

9. Assael, Ioannis Alexandros. Deep learning for communication : emergence, recognition and synthesis.

Degree: PhD, 2019, University of Oxford

 Human intelligence is a social phenomenon tightly coupled to the act and process of communication. Ever since the early prehistoric period, humans have been able… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Assael, I. A. (2019). Deep learning for communication : emergence, recognition and synthesis. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:794592eb-d957-49c4-8d46-c4eb19bd0125 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799986

Chicago Manual of Style (16th Edition):

Assael, Ioannis Alexandros. “Deep learning for communication : emergence, recognition and synthesis.” 2019. Doctoral Dissertation, University of Oxford. Accessed September 18, 2020. http://ora.ox.ac.uk/objects/uuid:794592eb-d957-49c4-8d46-c4eb19bd0125 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799986.

MLA Handbook (7th Edition):

Assael, Ioannis Alexandros. “Deep learning for communication : emergence, recognition and synthesis.” 2019. Web. 18 Sep 2020.

Vancouver:

Assael IA. Deep learning for communication : emergence, recognition and synthesis. [Internet] [Doctoral dissertation]. University of Oxford; 2019. [cited 2020 Sep 18]. Available from: http://ora.ox.ac.uk/objects/uuid:794592eb-d957-49c4-8d46-c4eb19bd0125 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799986.

Council of Science Editors:

Assael IA. Deep learning for communication : emergence, recognition and synthesis. [Doctoral Dissertation]. University of Oxford; 2019. Available from: http://ora.ox.ac.uk/objects/uuid:794592eb-d957-49c4-8d46-c4eb19bd0125 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799986

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

Degree: 2015, NC Docks

 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. (Thesis). NC Docks. Retrieved from http://libres.uncg.edu/ir/uncg/f/AlHamadani_uncg_0154M_11725.pdf

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):

Al-Hamadani, Mokhaled N A. “Evaluation of the performance of deep learning techniques over tampered dataset.” 2015. Thesis, NC Docks. Accessed September 18, 2020. http://libres.uncg.edu/ir/uncg/f/AlHamadani_uncg_0154M_11725.pdf.

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

MLA Handbook (7th Edition):

Al-Hamadani, Mokhaled N A. “Evaluation of the performance of deep learning techniques over tampered dataset.” 2015. Web. 18 Sep 2020.

Vancouver:

Al-Hamadani MNA. Evaluation of the performance of deep learning techniques over tampered dataset. [Internet] [Thesis]. NC Docks; 2015. [cited 2020 Sep 18]. Available from: http://libres.uncg.edu/ir/uncg/f/AlHamadani_uncg_0154M_11725.pdf.

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

Council of Science Editors:

Al-Hamadani MNA. Evaluation of the performance of deep learning techniques over tampered dataset. [Thesis]. NC Docks; 2015. Available from: http://libres.uncg.edu/ir/uncg/f/AlHamadani_uncg_0154M_11725.pdf

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

11. 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 (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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792658/.

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

MLA Handbook (7th Edition):

Khorshidi, Alireza. “Methods and Theories in Atomistic Reaction Engineering.” 2018. Web. 18 Sep 2020.

Vancouver:

Khorshidi A. Methods and Theories in Atomistic Reaction Engineering. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Sep 18]. 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

12. 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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:733405/.

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

MLA Handbook (7th Edition):

Lee, Seungjoon. “Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics.” 2017. Web. 18 Sep 2020.

Vancouver:

Lee S. Statistical Learning Tools for Information Fusion in Computational Fluid Dynamics. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Sep 18]. 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

13. 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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792905/.

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

MLA Handbook (7th Edition):

Brawner, Stephen Andrew. “Algorithms for the Personalization of AI for Robots and the Smart Home.” 2018. Web. 18 Sep 2020.

Vancouver:

Brawner SA. Algorithms for the Personalization of AI for Robots and the Smart Home. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Sep 18]. 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

14. 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 (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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792720/.

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

MLA Handbook (7th Edition):

Wang, Yinong. “Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks.” 2018. Web. 18 Sep 2020.

Vancouver:

Wang Y. Decoding hindlimb kinematics from primate motor cortex using long short-term memory recurrent neural networks. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Sep 18]. 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

15. 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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:733471/.

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

MLA Handbook (7th Edition):

Patil, Prerna. “Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder.” 2017. Web. 18 Sep 2020.

Vancouver:

Patil P. Multi-Fidelity Simulation Algorithm and its Application to Flow over a Cylinder. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Sep 18]. 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

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

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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:733424/.

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

MLA Handbook (7th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Web. 18 Sep 2020.

Vancouver:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Sep 18]. 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

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

Degree: Department of Computer Science, 2017, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Thesis, Brown University. Accessed September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792615/.

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

MLA Handbook (7th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Web. 18 Sep 2020.

Vancouver:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Sep 18]. 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

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

Degree: Department of Computer Science, 2018, Brown University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Thesis, Brown University. Accessed September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792891/.

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

MLA Handbook (7th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Web. 18 Sep 2020.

Vancouver:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Internet] [Thesis]. Brown University; 2018. [cited 2020 Sep 18]. 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

19. 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 September 18, 2020. https://repository.library.brown.edu/studio/item/bdr:792611/.

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

MLA Handbook (7th Edition):

Tang, Yu-Hang. “Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning.” 2017. Web. 18 Sep 2020.

Vancouver:

Tang Y. Multiscale and Mesoscopic Modeling of Soft Matter and Biophysical Systems Using High Performance Computing and Machine Learning. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Sep 18]. 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


University of Waikato

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

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 September 18, 2020. http://hdl.handle.net/10289/5701.

MLA Handbook (7th Edition):

Han, Zhimeng. “Smoothing in Probability Estimation Trees .” 2011. Web. 18 Sep 2020.

Vancouver:

Han Z. Smoothing in Probability Estimation Trees . [Internet] [Masters thesis]. University of Waikato; 2011. [cited 2020 Sep 18]. 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


Wake Forest University

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

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 September 18, 2020. 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. 18 Sep 2020.

Vancouver:

Patel U. Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture. [Internet] [Thesis]. Wake Forest University; 2016. [cited 2020 Sep 18]. 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


Oregon State University

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

Degree: PhD, 2017, Oregon State University

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

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Doctoral Dissertation, Oregon State University. Accessed September 18, 2020. http://hdl.handle.net/1957/61580.

MLA Handbook (7th Edition):

Das, Shubhomoy. “Incorporating User Feedback into Machine Learning Systems.” 2017. Web. 18 Sep 2020.

Vancouver:

Das S. Incorporating User Feedback into Machine Learning Systems. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2020 Sep 18]. 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 North Carolina – Greensboro

23. 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 September 18, 2020. 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. 18 Sep 2020.

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 2020 Sep 18]. 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


University of Oxford

24. McLeod, Mark. Optimizing Bayesian optimization.

Degree: PhD, 2018, University of Oxford

 We are concerned primarily with improving the practical applicability of Bayesian optimization. We make contributions in three key areas. We develop an intuitive online stopping… (more)

Subjects/Keywords: Machine learning

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

APA (6th Edition):

McLeod, M. (2018). Optimizing Bayesian optimization. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:c35f26ba-07ec-4830-ac37-39b37d36a8b3 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.786122

Chicago Manual of Style (16th Edition):

McLeod, Mark. “Optimizing Bayesian optimization.” 2018. Doctoral Dissertation, University of Oxford. Accessed September 18, 2020. http://ora.ox.ac.uk/objects/uuid:c35f26ba-07ec-4830-ac37-39b37d36a8b3 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.786122.

MLA Handbook (7th Edition):

McLeod, Mark. “Optimizing Bayesian optimization.” 2018. Web. 18 Sep 2020.

Vancouver:

McLeod M. Optimizing Bayesian optimization. [Internet] [Doctoral dissertation]. University of Oxford; 2018. [cited 2020 Sep 18]. Available from: http://ora.ox.ac.uk/objects/uuid:c35f26ba-07ec-4830-ac37-39b37d36a8b3 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.786122.

Council of Science Editors:

McLeod M. Optimizing Bayesian optimization. [Doctoral Dissertation]. University of Oxford; 2018. Available from: http://ora.ox.ac.uk/objects/uuid:c35f26ba-07ec-4830-ac37-39b37d36a8b3 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.786122


Universitetet i Tromsø

25. Myhre, Jonas Nordhaug. Machine Learning using Principal Manifolds and Mode Seeking .

Degree: 2016, Universitetet i Tromsø

 A wide range of machine learning methods have taken advantage of density estimates and their derivatives, including methodology related to principal manifolds and mode seeking,… (more)

Subjects/Keywords: Machine Learning

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

APA (6th Edition):

Myhre, J. N. (2016). Machine Learning using Principal Manifolds and Mode Seeking . (Doctoral Dissertation). Universitetet i Tromsø. Retrieved from http://hdl.handle.net/10037/9921

Chicago Manual of Style (16th Edition):

Myhre, Jonas Nordhaug. “Machine Learning using Principal Manifolds and Mode Seeking .” 2016. Doctoral Dissertation, Universitetet i Tromsø. Accessed September 18, 2020. http://hdl.handle.net/10037/9921.

MLA Handbook (7th Edition):

Myhre, Jonas Nordhaug. “Machine Learning using Principal Manifolds and Mode Seeking .” 2016. Web. 18 Sep 2020.

Vancouver:

Myhre JN. Machine Learning using Principal Manifolds and Mode Seeking . [Internet] [Doctoral dissertation]. Universitetet i Tromsø 2016. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/10037/9921.

Council of Science Editors:

Myhre JN. Machine Learning using Principal Manifolds and Mode Seeking . [Doctoral Dissertation]. Universitetet i Tromsø 2016. Available from: http://hdl.handle.net/10037/9921

26. 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 September 18, 2020. 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. 18 Sep 2020.

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 2020 Sep 18]. 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

27. 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 September 18, 2020. 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. 18 Sep 2020.

Vancouver:

Bacchelli A. Mining unstructured software data. [Internet] [Thesis]. Università della Svizzera italiana; 2013. [cited 2020 Sep 18]. 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


Rutgers University

28. Yoon, Sejong, 1980-. Generalized distributed learning under uncertainty for camera networks.

Degree: PhD, Computer Science, 2016, Rutgers University

Consensus-based distributed learning is a machine learning technique used to find the general consensus of local learning models to achieve a global objective. It is… (more)

Subjects/Keywords: Machine learning

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

APA (6th Edition):

Yoon, Sejong, 1. (2016). Generalized distributed learning under uncertainty for camera networks. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51518/

Chicago Manual of Style (16th Edition):

Yoon, Sejong, 1980-. “Generalized distributed learning under uncertainty for camera networks.” 2016. Doctoral Dissertation, Rutgers University. Accessed September 18, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51518/.

MLA Handbook (7th Edition):

Yoon, Sejong, 1980-. “Generalized distributed learning under uncertainty for camera networks.” 2016. Web. 18 Sep 2020.

Vancouver:

Yoon, Sejong 1. Generalized distributed learning under uncertainty for camera networks. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Sep 18]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51518/.

Council of Science Editors:

Yoon, Sejong 1. Generalized distributed learning under uncertainty for camera networks. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51518/


Rutgers University

29. Peng, Xi, 1986-. Learning disentangled representations in deep visual analysis.

Degree: PhD, Computer Science, 2018, Rutgers University

Learning reliable and interpretable representations is one of the fundamental challenges in machine learning and computer vision. Over the last decade, deep neural networks have… (more)

Subjects/Keywords: Machine learning

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

APA (6th Edition):

Peng, Xi, 1. (2018). Learning disentangled representations in deep visual analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/56078/

Chicago Manual of Style (16th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Doctoral Dissertation, Rutgers University. Accessed September 18, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

MLA Handbook (7th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Web. 18 Sep 2020.

Vancouver:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2020 Sep 18]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

Council of Science Editors:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/


Rutgers University

30. Al Mula Abd, Bilal, 1977-. Advanced machine learning algorithms in manufacturing scheduling problems.

Degree: PhD, Industrial and Systems Engineering, 2018, Rutgers University

 Scheduling is a master key to succeed in the manufacturing companies in global competition. Better process scheduling leads to competitive advantage by reducing production cost… (more)

Subjects/Keywords: Machine learning

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

APA (6th Edition):

Al Mula Abd, Bilal, 1. (2018). Advanced machine learning algorithms in manufacturing scheduling problems. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/58881/

Chicago Manual of Style (16th Edition):

Al Mula Abd, Bilal, 1977-. “Advanced machine learning algorithms in manufacturing scheduling problems.” 2018. Doctoral Dissertation, Rutgers University. Accessed September 18, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/58881/.

MLA Handbook (7th Edition):

Al Mula Abd, Bilal, 1977-. “Advanced machine learning algorithms in manufacturing scheduling problems.” 2018. Web. 18 Sep 2020.

Vancouver:

Al Mula Abd, Bilal 1. Advanced machine learning algorithms in manufacturing scheduling problems. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2020 Sep 18]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/58881/.

Council of Science Editors:

Al Mula Abd, Bilal 1. Advanced machine learning algorithms in manufacturing scheduling problems. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/58881/

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