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You searched for subject:(Distributed optimization). Showing records 1 – 30 of 424 total matches.

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University of Illinois – Urbana-Champaign

1. Phadke, Nishad Ashok. A framework for privacy-preserving, distributed machine learning using gradient obfuscation.

Degree: MS, Computer Science, 2017, University of Illinois – Urbana-Champaign

 Large-scale machine learning has recently risen to prominence in settings of both industry and academia, driven by today's newfound accessibility to data-collecting sensors and high-volume… (more)

Subjects/Keywords: Distributed optimization; Privacy

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

APA (6th Edition):

Phadke, N. A. (2017). A framework for privacy-preserving, distributed machine learning using gradient obfuscation. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/99116

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):

Phadke, Nishad Ashok. “A framework for privacy-preserving, distributed machine learning using gradient obfuscation.” 2017. Thesis, University of Illinois – Urbana-Champaign. Accessed October 23, 2020. http://hdl.handle.net/2142/99116.

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

MLA Handbook (7th Edition):

Phadke, Nishad Ashok. “A framework for privacy-preserving, distributed machine learning using gradient obfuscation.” 2017. Web. 23 Oct 2020.

Vancouver:

Phadke NA. A framework for privacy-preserving, distributed machine learning using gradient obfuscation. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2017. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/2142/99116.

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

Council of Science Editors:

Phadke NA. A framework for privacy-preserving, distributed machine learning using gradient obfuscation. [Thesis]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/99116

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


Rochester Institute of Technology

2. Li, Bo. Energy-aware replica selection for data-intensive services in cloud.

Degree: Computer Science (GCCIS), 2012, Rochester Institute of Technology

 With the increasing energy cost in data centers, an energy efficient approach to provide data intensive services in the cloud is highly in demand. This… (more)

Subjects/Keywords: Distributed optimization; Distributed systems; Replica selection

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APA (6th Edition):

Li, B. (2012). Energy-aware replica selection for data-intensive services in cloud. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/85

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):

Li, Bo. “Energy-aware replica selection for data-intensive services in cloud.” 2012. Thesis, Rochester Institute of Technology. Accessed October 23, 2020. https://scholarworks.rit.edu/theses/85.

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

MLA Handbook (7th Edition):

Li, Bo. “Energy-aware replica selection for data-intensive services in cloud.” 2012. Web. 23 Oct 2020.

Vancouver:

Li B. Energy-aware replica selection for data-intensive services in cloud. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2020 Oct 23]. Available from: https://scholarworks.rit.edu/theses/85.

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

Council of Science Editors:

Li B. Energy-aware replica selection for data-intensive services in cloud. [Thesis]. Rochester Institute of Technology; 2012. Available from: https://scholarworks.rit.edu/theses/85

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


Victoria University of Wellington

3. Jellyman, Dayle Raymond. Convex Optimization for Distributed Acoustic Beamforming.

Degree: 2017, Victoria University of Wellington

 Beamforming filter optimization can be performed over a distributed wireless sensor network, but the output calculation remains either centralized or linked in time to the… (more)

Subjects/Keywords: Distributed; Beamforming; Convex optimization

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APA (6th Edition):

Jellyman, D. R. (2017). Convex Optimization for Distributed Acoustic Beamforming. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/6650

Chicago Manual of Style (16th Edition):

Jellyman, Dayle Raymond. “Convex Optimization for Distributed Acoustic Beamforming.” 2017. Masters Thesis, Victoria University of Wellington. Accessed October 23, 2020. http://hdl.handle.net/10063/6650.

MLA Handbook (7th Edition):

Jellyman, Dayle Raymond. “Convex Optimization for Distributed Acoustic Beamforming.” 2017. Web. 23 Oct 2020.

Vancouver:

Jellyman DR. Convex Optimization for Distributed Acoustic Beamforming. [Internet] [Masters thesis]. Victoria University of Wellington; 2017. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/10063/6650.

Council of Science Editors:

Jellyman DR. Convex Optimization for Distributed Acoustic Beamforming. [Masters Thesis]. Victoria University of Wellington; 2017. Available from: http://hdl.handle.net/10063/6650


University of Illinois – Urbana-Champaign

4. Doan, Thinh Thanh. On the performance of distributed algorithms for network optimization problems.

Degree: PhD, Electrical & Computer Engr, 2018, University of Illinois – Urbana-Champaign

 This thesis considers optimization problems defined over a network of nodes, where each node knows only part of the objective functions. We are motivated by… (more)

Subjects/Keywords: Distributed algorithms; optimization; control theory

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APA (6th Edition):

Doan, T. T. (2018). On the performance of distributed algorithms for network optimization problems. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/100998

Chicago Manual of Style (16th Edition):

Doan, Thinh Thanh. “On the performance of distributed algorithms for network optimization problems.” 2018. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 23, 2020. http://hdl.handle.net/2142/100998.

MLA Handbook (7th Edition):

Doan, Thinh Thanh. “On the performance of distributed algorithms for network optimization problems.” 2018. Web. 23 Oct 2020.

Vancouver:

Doan TT. On the performance of distributed algorithms for network optimization problems. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2018. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/2142/100998.

Council of Science Editors:

Doan TT. On the performance of distributed algorithms for network optimization problems. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/100998


Delft University of Technology

5. Zeng, Yikai (author). Distributed Coordination for Multi-fleet Truck Platooning.

Degree: 2020, Delft University of Technology

Truck platooning refers to coordinating a group of heavy-duty vehicles at a close inter-vehicle distance to reduce overall fuel consumption. This coordination between trucks is… (more)

Subjects/Keywords: truck platooning; distributed optimization

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APA (6th Edition):

Zeng, Y. (. (2020). Distributed Coordination for Multi-fleet Truck Platooning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1a15878d-1e78-4db6-8c2f-07a09aeaa516

Chicago Manual of Style (16th Edition):

Zeng, Yikai (author). “Distributed Coordination for Multi-fleet Truck Platooning.” 2020. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:1a15878d-1e78-4db6-8c2f-07a09aeaa516.

MLA Handbook (7th Edition):

Zeng, Yikai (author). “Distributed Coordination for Multi-fleet Truck Platooning.” 2020. Web. 23 Oct 2020.

Vancouver:

Zeng Y(. Distributed Coordination for Multi-fleet Truck Platooning. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:1a15878d-1e78-4db6-8c2f-07a09aeaa516.

Council of Science Editors:

Zeng Y(. Distributed Coordination for Multi-fleet Truck Platooning. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:1a15878d-1e78-4db6-8c2f-07a09aeaa516


Georgia Tech

6. Zhou, Yi. Stochastic algorithms for distributed optimization and machine learning.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

 In the big data era, machine learning acts as a powerful tool to help us make predictions and decisions. It has strong ties to the… (more)

Subjects/Keywords: Randomized algorithms; Stochastic optimization; Distributed optimization; Machine learning; Distributed machine learning; Finite-sum optimization

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APA (6th Edition):

Zhou, Y. (2018). Stochastic algorithms for distributed optimization and machine learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60256

Chicago Manual of Style (16th Edition):

Zhou, Yi. “Stochastic algorithms for distributed optimization and machine learning.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2020. http://hdl.handle.net/1853/60256.

MLA Handbook (7th Edition):

Zhou, Yi. “Stochastic algorithms for distributed optimization and machine learning.” 2018. Web. 23 Oct 2020.

Vancouver:

Zhou Y. Stochastic algorithms for distributed optimization and machine learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1853/60256.

Council of Science Editors:

Zhou Y. Stochastic algorithms for distributed optimization and machine learning. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60256


Delft University of Technology

7. Zhang, H.M. (author). Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers.

Degree: 2015, Delft University of Technology

The Primal-Dual Method of Multipliers (PDMM) is a new algorithm that solves convex optimization problems in a distributed manner. This study focuses on the convergence… (more)

Subjects/Keywords: convex optimization; distributed signal processing; ADMM; PDMM

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APA (6th Edition):

Zhang, H. M. (. (2015). Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b

Chicago Manual of Style (16th Edition):

Zhang, H M (author). “Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers.” 2015. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b.

MLA Handbook (7th Edition):

Zhang, H M (author). “Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers.” 2015. Web. 23 Oct 2020.

Vancouver:

Zhang HM(. Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b.

Council of Science Editors:

Zhang HM(. Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b


University of Toronto

8. Srikantha, Pirathayini. Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations.

Degree: PhD, 2017, University of Toronto

 Today's electric grid is rapidly evolving to provision for heterogeneous system components (e.g. intermittent generation, electric vehicles, storage devices, etc.) while catering to diverse consumer… (more)

Subjects/Keywords: Distributed Optimization; Game theory; Sustainability; 0537

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APA (6th Edition):

Srikantha, P. (2017). Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/79482

Chicago Manual of Style (16th Edition):

Srikantha, Pirathayini. “Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations.” 2017. Doctoral Dissertation, University of Toronto. Accessed October 23, 2020. http://hdl.handle.net/1807/79482.

MLA Handbook (7th Edition):

Srikantha, Pirathayini. “Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations.” 2017. Web. 23 Oct 2020.

Vancouver:

Srikantha P. Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations. [Internet] [Doctoral dissertation]. University of Toronto; 2017. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1807/79482.

Council of Science Editors:

Srikantha P. Distributed Optimization of Sustainable Power Dispatch and Flexible Consumer Loads for Resilient Power Grid Operations. [Doctoral Dissertation]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/79482

9. Wu, Xiaofan. Sparsity-promoting optimal control of power networks.

Degree: PhD, Electrical/Computer Engineering, 2016, University of Minnesota

 In this dissertation, we study the problems of structure design and optimal control of consensus and synchronization networks. Our objective is to design controller that… (more)

Subjects/Keywords: control; distributed systems; optimization; power systems

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APA (6th Edition):

Wu, X. (2016). Sparsity-promoting optimal control of power networks. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/185164

Chicago Manual of Style (16th Edition):

Wu, Xiaofan. “Sparsity-promoting optimal control of power networks.” 2016. Doctoral Dissertation, University of Minnesota. Accessed October 23, 2020. http://hdl.handle.net/11299/185164.

MLA Handbook (7th Edition):

Wu, Xiaofan. “Sparsity-promoting optimal control of power networks.” 2016. Web. 23 Oct 2020.

Vancouver:

Wu X. Sparsity-promoting optimal control of power networks. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/11299/185164.

Council of Science Editors:

Wu X. Sparsity-promoting optimal control of power networks. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/185164

10. Patvarczki, Jozsef. Layout Optimization for Distributed Relational Databases Using Machine Learning.

Degree: PhD, 2012, Worcester Polytechnic Institute

 A common problem when running Web-based applications is how to scale-up the database. The solution to this problem usually involves having a smart Database Administrator… (more)

Subjects/Keywords: distributed databases; machine learning; layout optimization

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APA (6th Edition):

Patvarczki, J. (2012). Layout Optimization for Distributed Relational Databases Using Machine Learning. (Doctoral Dissertation). Worcester Polytechnic Institute. Retrieved from etd-052312-120132 ; https://digitalcommons.wpi.edu/etd-dissertations/291

Chicago Manual of Style (16th Edition):

Patvarczki, Jozsef. “Layout Optimization for Distributed Relational Databases Using Machine Learning.” 2012. Doctoral Dissertation, Worcester Polytechnic Institute. Accessed October 23, 2020. etd-052312-120132 ; https://digitalcommons.wpi.edu/etd-dissertations/291.

MLA Handbook (7th Edition):

Patvarczki, Jozsef. “Layout Optimization for Distributed Relational Databases Using Machine Learning.” 2012. Web. 23 Oct 2020.

Vancouver:

Patvarczki J. Layout Optimization for Distributed Relational Databases Using Machine Learning. [Internet] [Doctoral dissertation]. Worcester Polytechnic Institute; 2012. [cited 2020 Oct 23]. Available from: etd-052312-120132 ; https://digitalcommons.wpi.edu/etd-dissertations/291.

Council of Science Editors:

Patvarczki J. Layout Optimization for Distributed Relational Databases Using Machine Learning. [Doctoral Dissertation]. Worcester Polytechnic Institute; 2012. Available from: etd-052312-120132 ; https://digitalcommons.wpi.edu/etd-dissertations/291


Carnegie Mellon University

11. Dai, Wei. Learning with Staleness.

Degree: 2018, Carnegie Mellon University

 A fundamental assumption behind most machine learning (ML) algorithms and analyses is the sequential execution. That is, any update to the ML model can be… (more)

Subjects/Keywords: Large Scale Machine Learning; Distributed Optimization Method; Distributed System; Parameter Server

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APA (6th Edition):

Dai, W. (2018). Learning with Staleness. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1209

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):

Dai, Wei. “Learning with Staleness.” 2018. Thesis, Carnegie Mellon University. Accessed October 23, 2020. http://repository.cmu.edu/dissertations/1209.

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

MLA Handbook (7th Edition):

Dai, Wei. “Learning with Staleness.” 2018. Web. 23 Oct 2020.

Vancouver:

Dai W. Learning with Staleness. [Internet] [Thesis]. Carnegie Mellon University; 2018. [cited 2020 Oct 23]. Available from: http://repository.cmu.edu/dissertations/1209.

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

Council of Science Editors:

Dai W. Learning with Staleness. [Thesis]. Carnegie Mellon University; 2018. Available from: http://repository.cmu.edu/dissertations/1209

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


Queens University

12. Ebegbulem, Judith. Distributed control of multi-agent systems using extremum seeking .

Degree: Chemical Engineering, 2016, Queens University

 A model free control technique (extremum seeking) is employed to address problems of large-scale systems involving multi-agents in real-time. This thesis focuses on the use… (more)

Subjects/Keywords: Multi-agent systems ; Distributed control ; Extremum seeking control ; Distributed optimization

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APA (6th Edition):

Ebegbulem, J. (2016). Distributed control of multi-agent systems using extremum seeking . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14167

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):

Ebegbulem, Judith. “Distributed control of multi-agent systems using extremum seeking .” 2016. Thesis, Queens University. Accessed October 23, 2020. http://hdl.handle.net/1974/14167.

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

MLA Handbook (7th Edition):

Ebegbulem, Judith. “Distributed control of multi-agent systems using extremum seeking .” 2016. Web. 23 Oct 2020.

Vancouver:

Ebegbulem J. Distributed control of multi-agent systems using extremum seeking . [Internet] [Thesis]. Queens University; 2016. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1974/14167.

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

Council of Science Editors:

Ebegbulem J. Distributed control of multi-agent systems using extremum seeking . [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14167

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


University of Minnesota

13. Tang, Wentao. Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence.

Degree: PhD, Chemical Engineering, 2020, University of Minnesota

 Chemical processes are intrinsically nonlinear and often integrated into large-scale networks, which are difficult to control effectively. The traditional challenges faced by process control, as… (more)

Subjects/Keywords: Data-driven control; Distributed control; Distributed optimization; Nonlinear systems; Process control

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APA (6th Edition):

Tang, W. (2020). Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/215092

Chicago Manual of Style (16th Edition):

Tang, Wentao. “Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence.” 2020. Doctoral Dissertation, University of Minnesota. Accessed October 23, 2020. http://hdl.handle.net/11299/215092.

MLA Handbook (7th Edition):

Tang, Wentao. “Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence.” 2020. Web. 23 Oct 2020.

Vancouver:

Tang W. Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence. [Internet] [Doctoral dissertation]. University of Minnesota; 2020. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/11299/215092.

Council of Science Editors:

Tang W. Methods Of Distributed And Nonlinear Process Control: Structuredness, Optimality And Intelligence. [Doctoral Dissertation]. University of Minnesota; 2020. Available from: http://hdl.handle.net/11299/215092


NSYSU

14. Huang, Bo-chi. Distributed Spiral Optimization: Using Clustering as a Case.

Degree: Master, Computer Science and Engineering, 2013, NSYSU

 Nowadays, metaheuristics have become more and more important in solving the combinatorial optimization problems (COPs) for which the traditional methods (such as k-means, tabu search,… (more)

Subjects/Keywords: metaheuristic; spiral optimization; clustering; sensitivity analysis; distributed spiral optimization

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APA (6th Edition):

Huang, B. (2013). Distributed Spiral Optimization: Using Clustering as a Case. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630113-105958

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):

Huang, Bo-chi. “Distributed Spiral Optimization: Using Clustering as a Case.” 2013. Thesis, NSYSU. Accessed October 23, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630113-105958.

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

MLA Handbook (7th Edition):

Huang, Bo-chi. “Distributed Spiral Optimization: Using Clustering as a Case.” 2013. Web. 23 Oct 2020.

Vancouver:

Huang B. Distributed Spiral Optimization: Using Clustering as a Case. [Internet] [Thesis]. NSYSU; 2013. [cited 2020 Oct 23]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630113-105958.

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

Council of Science Editors:

Huang B. Distributed Spiral Optimization: Using Clustering as a Case. [Thesis]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630113-105958

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


Carnegie Mellon University

15. Reddi, Sashank Jakkam. New Optimization Methods for Modern Machine Learning.

Degree: 2017, Carnegie Mellon University

 Modern machine learning systems pose several new statistical, scalability, privacy and ethical challenges. With the advent of massive datasets and increasingly complex tasks, scalability has… (more)

Subjects/Keywords: Machine Learning; Optimization; Large-scale; Distributed optimization; Communication-efficient; Finite-sum

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APA (6th Edition):

Reddi, S. J. (2017). New Optimization Methods for Modern Machine Learning. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1116

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):

Reddi, Sashank Jakkam. “New Optimization Methods for Modern Machine Learning.” 2017. Thesis, Carnegie Mellon University. Accessed October 23, 2020. http://repository.cmu.edu/dissertations/1116.

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

MLA Handbook (7th Edition):

Reddi, Sashank Jakkam. “New Optimization Methods for Modern Machine Learning.” 2017. Web. 23 Oct 2020.

Vancouver:

Reddi SJ. New Optimization Methods for Modern Machine Learning. [Internet] [Thesis]. Carnegie Mellon University; 2017. [cited 2020 Oct 23]. Available from: http://repository.cmu.edu/dissertations/1116.

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

Council of Science Editors:

Reddi SJ. New Optimization Methods for Modern Machine Learning. [Thesis]. Carnegie Mellon University; 2017. Available from: http://repository.cmu.edu/dissertations/1116

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


Delft University of Technology

16. van Dam, Floris (author). Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation.

Degree: 2019, Delft University of Technology

In recent years there has been an increasing interest in formation flying with many lightweight spacecraft, as satellite missions can potentially become cheaper and more… (more)

Subjects/Keywords: Distributed optimization; Collision Avoidance; Spacecraft; Formation Flight; Trajectory optimization

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APA (6th Edition):

van Dam, F. (. (2019). Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e1b6dbe5-e7cd-4aad-b8c6-ffbdeb5654a1

Chicago Manual of Style (16th Edition):

van Dam, Floris (author). “Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation.” 2019. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:e1b6dbe5-e7cd-4aad-b8c6-ffbdeb5654a1.

MLA Handbook (7th Edition):

van Dam, Floris (author). “Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation.” 2019. Web. 23 Oct 2020.

Vancouver:

van Dam F(. Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:e1b6dbe5-e7cd-4aad-b8c6-ffbdeb5654a1.

Council of Science Editors:

van Dam F(. Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:e1b6dbe5-e7cd-4aad-b8c6-ffbdeb5654a1


UCLA

17. Towfic, Zaid Joseph. Online Learning Over Networks.

Degree: Electrical Engineering, 2014, UCLA

Distributed convex optimization refers to the task of minimizing the aggregate sum of convex risk functions, each available at an agent of a connected network,… (more)

Subjects/Keywords: Electrical engineering; Computer science; diffusion strategies; distributed optimization; online learning; optimization; stochastic optimization

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APA (6th Edition):

Towfic, Z. J. (2014). Online Learning Over Networks. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/15w589fn

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):

Towfic, Zaid Joseph. “Online Learning Over Networks.” 2014. Thesis, UCLA. Accessed October 23, 2020. http://www.escholarship.org/uc/item/15w589fn.

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

MLA Handbook (7th Edition):

Towfic, Zaid Joseph. “Online Learning Over Networks.” 2014. Web. 23 Oct 2020.

Vancouver:

Towfic ZJ. Online Learning Over Networks. [Internet] [Thesis]. UCLA; 2014. [cited 2020 Oct 23]. Available from: http://www.escholarship.org/uc/item/15w589fn.

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

Council of Science Editors:

Towfic ZJ. Online Learning Over Networks. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/15w589fn

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


Penn State University

18. Wang, Zi. First-Order Methods for Large Scale Convex Optimization.

Degree: 2016, Penn State University

 The revolution of storage technology in the past few decades made it possible to gather tremendous amount of data anywhere from demand and sales records… (more)

Subjects/Keywords: first-order methods; convex optimization; distributed optimization; convex regression; multi-agent consensus optimization

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APA (6th Edition):

Wang, Z. (2016). First-Order Methods for Large Scale Convex Optimization. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13485zxw121

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, Zi. “First-Order Methods for Large Scale Convex Optimization.” 2016. Thesis, Penn State University. Accessed October 23, 2020. https://submit-etda.libraries.psu.edu/catalog/13485zxw121.

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

MLA Handbook (7th Edition):

Wang, Zi. “First-Order Methods for Large Scale Convex Optimization.” 2016. Web. 23 Oct 2020.

Vancouver:

Wang Z. First-Order Methods for Large Scale Convex Optimization. [Internet] [Thesis]. Penn State University; 2016. [cited 2020 Oct 23]. Available from: https://submit-etda.libraries.psu.edu/catalog/13485zxw121.

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

Council of Science Editors:

Wang Z. First-Order Methods for Large Scale Convex Optimization. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/13485zxw121

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


Penn State University

19. Ahmadi, Hesamoddin. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.

Degree: 2016, Penn State University

 This dissertation considers the resolution of three optimization problems. Of these, the first two problems are closely related and focus on solving optimization problems in… (more)

Subjects/Keywords: Optimization and learning; distributed optimization in power system; convex optimization; augmented Lagrangian

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

APA (6th Edition):

Ahmadi, H. (2016). On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/29502

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):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Thesis, Penn State University. Accessed October 23, 2020. https://submit-etda.libraries.psu.edu/catalog/29502.

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

MLA Handbook (7th Edition):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Web. 23 Oct 2020.

Vancouver:

Ahmadi H. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. [Internet] [Thesis]. Penn State University; 2016. [cited 2020 Oct 23]. Available from: https://submit-etda.libraries.psu.edu/catalog/29502.

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

Council of Science Editors:

Ahmadi H. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/29502

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


Carnegie Mellon University

20. Guo, Junyao. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.

Degree: 2018, Carnegie Mellon University

 To integrate large volumes of renewables and use electricity more efficiently, many industrial trials are on-going around the world that aim to realize decentralized or… (more)

Subjects/Keywords: asynchronous optimization; distributed optimization; nonconvex optimization; optimal power flow; power system partitioning; smart grid communications

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APA (6th Edition):

Guo, J. (2018). Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1140

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):

Guo, Junyao. “Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.” 2018. Thesis, Carnegie Mellon University. Accessed October 23, 2020. http://repository.cmu.edu/dissertations/1140.

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

MLA Handbook (7th Edition):

Guo, Junyao. “Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.” 2018. Web. 23 Oct 2020.

Vancouver:

Guo J. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. [Internet] [Thesis]. Carnegie Mellon University; 2018. [cited 2020 Oct 23]. Available from: http://repository.cmu.edu/dissertations/1140.

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

Council of Science Editors:

Guo J. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. [Thesis]. Carnegie Mellon University; 2018. Available from: http://repository.cmu.edu/dissertations/1140

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


Iowa State University

21. Wang, Jing. Distributed averaging over communication networks:Fragility, robustness and opportunities.

Degree: 2011, Iowa State University

Distributed averaging, a canonical operation among many natural interconnected systems, has found applications in a tremendous variety of applied fields, including statistical physics, signal processing,… (more)

Subjects/Keywords: Consensus; Delays; Distributed Averaging; Distributed Optimization; Fading Channels; Levy Flight; Electrical and Computer Engineering

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APA (6th Edition):

Wang, J. (2011). Distributed averaging over communication networks:Fragility, robustness and opportunities. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/10119

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, Jing. “Distributed averaging over communication networks:Fragility, robustness and opportunities.” 2011. Thesis, Iowa State University. Accessed October 23, 2020. https://lib.dr.iastate.edu/etd/10119.

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

MLA Handbook (7th Edition):

Wang, Jing. “Distributed averaging over communication networks:Fragility, robustness and opportunities.” 2011. Web. 23 Oct 2020.

Vancouver:

Wang J. Distributed averaging over communication networks:Fragility, robustness and opportunities. [Internet] [Thesis]. Iowa State University; 2011. [cited 2020 Oct 23]. Available from: https://lib.dr.iastate.edu/etd/10119.

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

Council of Science Editors:

Wang J. Distributed averaging over communication networks:Fragility, robustness and opportunities. [Thesis]. Iowa State University; 2011. Available from: https://lib.dr.iastate.edu/etd/10119

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

22. Weerasinghe, Handuwala Dewage Dulan Jayanatha. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.

Degree: PhD, Electrical and Computer Engineering, 2015, Kansas State University

 Optimizing renewable distributed generation in distribution systems has gained popularity with changes in federal energy policies. Various studies have been reported in this regard and… (more)

Subjects/Keywords: Distributed wind generation; Distribution system; Distributed energy storage system; Optimization; Electrical Engineering (0544)

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APA (6th Edition):

Weerasinghe, H. D. D. J. (2015). Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/28714

Chicago Manual of Style (16th Edition):

Weerasinghe, Handuwala Dewage Dulan Jayanatha. “Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.” 2015. Doctoral Dissertation, Kansas State University. Accessed October 23, 2020. http://hdl.handle.net/2097/28714.

MLA Handbook (7th Edition):

Weerasinghe, Handuwala Dewage Dulan Jayanatha. “Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.” 2015. Web. 23 Oct 2020.

Vancouver:

Weerasinghe HDDJ. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. [Internet] [Doctoral dissertation]. Kansas State University; 2015. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/2097/28714.

Council of Science Editors:

Weerasinghe HDDJ. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. [Doctoral Dissertation]. Kansas State University; 2015. Available from: http://hdl.handle.net/2097/28714


The Ohio State University

23. Wang, Sinong. Coded Computation for Speeding up Distributed Machine Learning.

Degree: PhD, Electrical and Computer Engineering, 2019, The Ohio State University

 Large-scale machine learning has shown great promise for solving many practical applications. Such applications require massive training datasets and model parameters, and force practitioners to… (more)

Subjects/Keywords: Computer Science; Electrical Engineering; Machine learning; distributed computation; information theory; coding theory; distributed optimization

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APA (6th Edition):

Wang, S. (2019). Coded Computation for Speeding up Distributed Machine Learning. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1555336880521062

Chicago Manual of Style (16th Edition):

Wang, Sinong. “Coded Computation for Speeding up Distributed Machine Learning.” 2019. Doctoral Dissertation, The Ohio State University. Accessed October 23, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555336880521062.

MLA Handbook (7th Edition):

Wang, Sinong. “Coded Computation for Speeding up Distributed Machine Learning.” 2019. Web. 23 Oct 2020.

Vancouver:

Wang S. Coded Computation for Speeding up Distributed Machine Learning. [Internet] [Doctoral dissertation]. The Ohio State University; 2019. [cited 2020 Oct 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555336880521062.

Council of Science Editors:

Wang S. Coded Computation for Speeding up Distributed Machine Learning. [Doctoral Dissertation]. The Ohio State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555336880521062


University of Washington

24. Meng, De. Graph Design via Convex Optimization: Online and Distributed Perspectives.

Degree: PhD, 2017, University of Washington

 Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc.… (more)

Subjects/Keywords: Convex Optimization; Distributed Optimization; Geodesic Distance; Graph and Network; Numerical Optimization; Online Optimization; Electrical engineering; Mathematics; Electrical engineering

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

APA (6th Edition):

Meng, D. (2017). Graph Design via Convex Optimization: Online and Distributed Perspectives. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40058

Chicago Manual of Style (16th Edition):

Meng, De. “Graph Design via Convex Optimization: Online and Distributed Perspectives.” 2017. Doctoral Dissertation, University of Washington. Accessed October 23, 2020. http://hdl.handle.net/1773/40058.

MLA Handbook (7th Edition):

Meng, De. “Graph Design via Convex Optimization: Online and Distributed Perspectives.” 2017. Web. 23 Oct 2020.

Vancouver:

Meng D. Graph Design via Convex Optimization: Online and Distributed Perspectives. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1773/40058.

Council of Science Editors:

Meng D. Graph Design via Convex Optimization: Online and Distributed Perspectives. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40058


University of Alberta

25. Sahar, Movaghati. Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks.

Degree: PhD, Department of Electrical and Computer Engineering, 2014, University of Alberta

 In distributed sensing systems, measurements from a random process or parameter are usually not available in one place. Also, the processing resources are distributed over… (more)

Subjects/Keywords: distributed quantization; assignment problem; bayesian networks; distributed algorithm; distributed estimation; optimization; particle filtering; factor graph; wireless sensor network; mutual information

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APA (6th Edition):

Sahar, M. (2014). Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cxd07gs82z

Chicago Manual of Style (16th Edition):

Sahar, Movaghati. “Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks.” 2014. Doctoral Dissertation, University of Alberta. Accessed October 23, 2020. https://era.library.ualberta.ca/files/cxd07gs82z.

MLA Handbook (7th Edition):

Sahar, Movaghati. “Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks.” 2014. Web. 23 Oct 2020.

Vancouver:

Sahar M. Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks. [Internet] [Doctoral dissertation]. University of Alberta; 2014. [cited 2020 Oct 23]. Available from: https://era.library.ualberta.ca/files/cxd07gs82z.

Council of Science Editors:

Sahar M. Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks. [Doctoral Dissertation]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/cxd07gs82z


Delft University of Technology

26. Simonetto, A. Distributed Estimation and Control for Robotic Networks.

Degree: 2012, Delft University of Technology

 Mobile robots that communicate and cooperate to achieve a common task have been the subject of an increasing research interest in recent years. These possibly… (more)

Subjects/Keywords: Distributed Optimization; Robotics; Sensor Networks; Distributed Control; Distributed Estimation

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APA (6th Edition):

Simonetto, A. (2012). Distributed Estimation and Control for Robotic Networks. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3

Chicago Manual of Style (16th Edition):

Simonetto, A. “Distributed Estimation and Control for Robotic Networks.” 2012. Doctoral Dissertation, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3.

MLA Handbook (7th Edition):

Simonetto, A. “Distributed Estimation and Control for Robotic Networks.” 2012. Web. 23 Oct 2020.

Vancouver:

Simonetto A. Distributed Estimation and Control for Robotic Networks. [Internet] [Doctoral dissertation]. Delft University of Technology; 2012. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3.

Council of Science Editors:

Simonetto A. Distributed Estimation and Control for Robotic Networks. [Doctoral Dissertation]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; urn:NBN:nl:ui:24-uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3 ; http://resolver.tudelft.nl/uuid:5813eccb-4292-4fbf-8dbe-b0d31bdaede3


University of Illinois – Urbana-Champaign

27. Robbins, Brett Andrew. Architectures and algorithms for voltage control in power distribution systems.

Degree: PhD, Electrical & Computer Engr, 2015, University of Illinois – Urbana-Champaign

 In this thesis, we propose a hierarchical control architecture for voltage in power distribution networks where there is a separation between the slow time-scale, in… (more)

Subjects/Keywords: Power Systems; Power Distribution Systems; Voltage Regulation; Optimization; Distributed Optimization; Optimal Power Flow; Convex Relaxation; Distributed Energy Resources

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APA (6th Edition):

Robbins, B. A. (2015). Architectures and algorithms for voltage control in power distribution systems. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78592

Chicago Manual of Style (16th Edition):

Robbins, Brett Andrew. “Architectures and algorithms for voltage control in power distribution systems.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 23, 2020. http://hdl.handle.net/2142/78592.

MLA Handbook (7th Edition):

Robbins, Brett Andrew. “Architectures and algorithms for voltage control in power distribution systems.” 2015. Web. 23 Oct 2020.

Vancouver:

Robbins BA. Architectures and algorithms for voltage control in power distribution systems. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/2142/78592.

Council of Science Editors:

Robbins BA. Architectures and algorithms for voltage control in power distribution systems. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78592


Queens University

28. Akbari Varnousfaderani, Mohammad Jr. Distributed Online Optimization on time-varying networks .

Degree: Mathematics and Statistics, 2015, Queens University

 This thesis introduces two classes of discrete-time distributed online optimization algorithms, with a group of agents which communicate over a network. At each time, a… (more)

Subjects/Keywords: Multi-agent Systems ; Sensor Networks ; Distributed Optimization ; Subgradient Algorithm ; Method of Multipliers ; Online Optimization

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APA (6th Edition):

Akbari Varnousfaderani, M. J. (2015). Distributed Online Optimization on time-varying networks . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/13551

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):

Akbari Varnousfaderani, Mohammad Jr. “Distributed Online Optimization on time-varying networks .” 2015. Thesis, Queens University. Accessed October 23, 2020. http://hdl.handle.net/1974/13551.

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

MLA Handbook (7th Edition):

Akbari Varnousfaderani, Mohammad Jr. “Distributed Online Optimization on time-varying networks .” 2015. Web. 23 Oct 2020.

Vancouver:

Akbari Varnousfaderani MJ. Distributed Online Optimization on time-varying networks . [Internet] [Thesis]. Queens University; 2015. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1974/13551.

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

Council of Science Editors:

Akbari Varnousfaderani MJ. Distributed Online Optimization on time-varying networks . [Thesis]. Queens University; 2015. Available from: http://hdl.handle.net/1974/13551

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


Rice University

29. Sharma, Kamal Gopal. Locality Transformations of Computation and Data for Portable Performance.

Degree: PhD, Engineering, 2014, Rice University

 Recently, multi-cores chips have become omnipresent in computer systems ranging from high-end servers to mobile phones. A variety of multi-core architectures have been developed which… (more)

Subjects/Keywords: Locality Transformations; Cache Optimization; Tile size selection; Data Layout Optimization; Performance; Distributed Function Selection

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APA (6th Edition):

Sharma, K. G. (2014). Locality Transformations of Computation and Data for Portable Performance. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/88159

Chicago Manual of Style (16th Edition):

Sharma, Kamal Gopal. “Locality Transformations of Computation and Data for Portable Performance.” 2014. Doctoral Dissertation, Rice University. Accessed October 23, 2020. http://hdl.handle.net/1911/88159.

MLA Handbook (7th Edition):

Sharma, Kamal Gopal. “Locality Transformations of Computation and Data for Portable Performance.” 2014. Web. 23 Oct 2020.

Vancouver:

Sharma KG. Locality Transformations of Computation and Data for Portable Performance. [Internet] [Doctoral dissertation]. Rice University; 2014. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/1911/88159.

Council of Science Editors:

Sharma KG. Locality Transformations of Computation and Data for Portable Performance. [Doctoral Dissertation]. Rice University; 2014. Available from: http://hdl.handle.net/1911/88159


Delft University of Technology

30. de Luis, R.H. (author). Optimal Placement and Sizing of Distributed Generation.

Degree: 2016, Delft University of Technology

In this thesis work we solve the problem of optimal placement and sizing of distributed generation by using an original Fuzzy Adaptive Particle Swarm Optimization(more)

Subjects/Keywords: Distributed Generation; Investment Planning; Microgrids; Distribution Networks; Optimization; Particle Swarm Optimization; Linear Programming

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APA (6th Edition):

de Luis, R. H. (. (2016). Optimal Placement and Sizing of Distributed Generation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:28671d8a-a00a-4526-a670-0c1e80ad50ff

Chicago Manual of Style (16th Edition):

de Luis, R H (author). “Optimal Placement and Sizing of Distributed Generation.” 2016. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:28671d8a-a00a-4526-a670-0c1e80ad50ff.

MLA Handbook (7th Edition):

de Luis, R H (author). “Optimal Placement and Sizing of Distributed Generation.” 2016. Web. 23 Oct 2020.

Vancouver:

de Luis RH(. Optimal Placement and Sizing of Distributed Generation. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:28671d8a-a00a-4526-a670-0c1e80ad50ff.

Council of Science Editors:

de Luis RH(. Optimal Placement and Sizing of Distributed Generation. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:28671d8a-a00a-4526-a670-0c1e80ad50ff

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