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374 total matches.

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- 2009 – 2013 (124)
- 2004 – 2008 (29)

Universities

Department

- Mathematics (14)
- Electrical Engineering (13)
- Electrical and Computer Engineering (12)
- Industrial and Systems Engineering (11)
- Informatique (10)
- Mathématiques appliquées (10)

Degrees

- PhD (92)
- Docteur es (48)
- MS (10)
- Master (10)

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1.
Uthayakumar, R.
Study on convergence of *optimization* problems;.

Degree: 2014, INFLIBNET

URL: http://shodhganga.inflibnet.ac.in/handle/10603/17964

►

In this thesis, various notions of convergence of sequence of sets and functions and their applications in the convergence of the optimal values under the… (more)

Subjects/Keywords: Convergence; Convex; Functions; Non-convex; Optimization; Sets

Record Details Similar Records

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

APA (6^{th} Edition):

Uthayakumar, R. (2014). Study on convergence of optimization problems;. (Thesis). INFLIBNET. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/17964

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Uthayakumar, R. “Study on convergence of optimization problems;.” 2014. Thesis, INFLIBNET. Accessed December 18, 2018. http://shodhganga.inflibnet.ac.in/handle/10603/17964.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Uthayakumar, R. “Study on convergence of optimization problems;.” 2014. Web. 18 Dec 2018.

Vancouver:

Uthayakumar R. Study on convergence of optimization problems;. [Internet] [Thesis]. INFLIBNET; 2014. [cited 2018 Dec 18]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17964.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Uthayakumar R. Study on convergence of optimization problems;. [Thesis]. INFLIBNET; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17964

Not specified: Masters Thesis or Doctoral Dissertation

Victoria University of Wellington

2.
Jellyman, Dayle Raymond.
*Convex**Optimization* for Distributed Acoustic Beamforming.

Degree: 2017, Victoria University of Wellington

URL: http://hdl.handle.net/10063/6650

► 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

Record Details Similar Records

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APA (6^{th} 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 (16^{th} Edition):

Jellyman, Dayle Raymond. “Convex Optimization for Distributed Acoustic Beamforming.” 2017. Masters Thesis, Victoria University of Wellington. Accessed December 18, 2018. http://hdl.handle.net/10063/6650.

MLA Handbook (7^{th} Edition):

Jellyman, Dayle Raymond. “Convex Optimization for Distributed Acoustic Beamforming.” 2017. Web. 18 Dec 2018.

Vancouver:

Jellyman DR. Convex Optimization for Distributed Acoustic Beamforming. [Internet] [Masters thesis]. Victoria University of Wellington; 2017. [cited 2018 Dec 18]. 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

NSYSU

3. Zhang, Shu-Bin. Study on Digital Filter Design and Coefficient Quantization.

Degree: Master, Communications Engineering, 2011, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727111-135237

► In this thesis, the basic theory is *convex* *optimization* theory[1]. And we study the problem about how to transfer to *convex* *optimization* problem from the…
(more)

Subjects/Keywords: Filter; Optimization; Convex; Bits; Quantization

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APA (6^{th} Edition):

Zhang, S. (2011). Study on Digital Filter Design and Coefficient Quantization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727111-135237

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Zhang, Shu-Bin. “Study on Digital Filter Design and Coefficient Quantization.” 2011. Thesis, NSYSU. Accessed December 18, 2018. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727111-135237.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Zhang, Shu-Bin. “Study on Digital Filter Design and Coefficient Quantization.” 2011. Web. 18 Dec 2018.

Vancouver:

Zhang S. Study on Digital Filter Design and Coefficient Quantization. [Internet] [Thesis]. NSYSU; 2011. [cited 2018 Dec 18]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727111-135237.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang S. Study on Digital Filter Design and Coefficient Quantization. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727111-135237

Not specified: Masters Thesis or Doctoral Dissertation

Princeton University

4.
Ma, Tengyu.
Non-*convex* *Optimization* for Machine Learning: Design, Analysis, and Understanding
.

Degree: PhD, 2017, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp01th83m199d

► Non-*convex* *optimization* is ubiquitous in modern machine learning: recent breakthroughs in deep learning require optimizing non-*convex* training objective functions; problems that admit accurate *convex* relaxation…
(more)

Subjects/Keywords: machine learning; non-convex optimization

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APA (6^{th} Edition):

Ma, T. (2017). Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01th83m199d

Chicago Manual of Style (16^{th} Edition):

Ma, Tengyu. “Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding .” 2017. Doctoral Dissertation, Princeton University. Accessed December 18, 2018. http://arks.princeton.edu/ark:/88435/dsp01th83m199d.

MLA Handbook (7^{th} Edition):

Ma, Tengyu. “Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding .” 2017. Web. 18 Dec 2018.

Vancouver:

Ma T. Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2018 Dec 18]. Available from: http://arks.princeton.edu/ark:/88435/dsp01th83m199d.

Council of Science Editors:

Ma T. Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp01th83m199d

5.
Cosentino, Alessandro.
Quantum State Local Distinguishability via *Convex* * Optimization*.

Degree: 2015, University of Waterloo

URL: http://hdl.handle.net/10012/9572

► Entanglement and nonlocality play a fundamental role in quantum computing. To understand the interplay between these phenomena, researchers have considered the model of local operations…
(more)

Subjects/Keywords: quantum information; convex optimization

Record Details Similar Records

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APA (6^{th} Edition):

Cosentino, A. (2015). Quantum State Local Distinguishability via Convex Optimization. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9572

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Cosentino, Alessandro. “Quantum State Local Distinguishability via Convex Optimization.” 2015. Thesis, University of Waterloo. Accessed December 18, 2018. http://hdl.handle.net/10012/9572.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Cosentino, Alessandro. “Quantum State Local Distinguishability via Convex Optimization.” 2015. Web. 18 Dec 2018.

Vancouver:

Cosentino A. Quantum State Local Distinguishability via Convex Optimization. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/10012/9572.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cosentino A. Quantum State Local Distinguishability via Convex Optimization. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9572

Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

6.
Wang, Ye, Ph. D.
Novel *convex* *optimization* techniques for circuit analysis and synthesis.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/67661

► Technology scaling brings about the need for computationally efficient methods for circuit analysis, *optimization*, and synthesis. *Convex* *optimization* is a special class of mathematical *optimization*…
(more)

Subjects/Keywords: Convex optimization; EDA problems

Record Details Similar Records

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

APA (6^{th} Edition):

Wang, Ye, P. D. (2018). Novel convex optimization techniques for circuit analysis and synthesis. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67661

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Wang, Ye, Ph D. “Novel convex optimization techniques for circuit analysis and synthesis.” 2018. Thesis, University of Texas – Austin. Accessed December 18, 2018. http://hdl.handle.net/2152/67661.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wang, Ye, Ph D. “Novel convex optimization techniques for circuit analysis and synthesis.” 2018. Web. 18 Dec 2018.

Vancouver:

Wang, Ye PD. Novel convex optimization techniques for circuit analysis and synthesis. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2152/67661.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang, Ye PD. Novel convex optimization techniques for circuit analysis and synthesis. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/67661

Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

7. Berning, Andrew Walter, Jr. Verification of successive convexification algorithm.

Degree: Aerospace Engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/41579

► In this report, I describe a technique which allows a non-*convex* optimal control problem to be expressed and solved in a *convex* manner. I then…
(more)

Subjects/Keywords: Convex; Convexification; Optimization; Verification

Record Details Similar Records

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

APA (6^{th} Edition):

Berning, Andrew Walter, J. (2016). Verification of successive convexification algorithm. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41579

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Berning, Andrew Walter, Jr. “Verification of successive convexification algorithm.” 2016. Thesis, University of Texas – Austin. Accessed December 18, 2018. http://hdl.handle.net/2152/41579.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Berning, Andrew Walter, Jr. “Verification of successive convexification algorithm.” 2016. Web. 18 Dec 2018.

Vancouver:

Berning, Andrew Walter J. Verification of successive convexification algorithm. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2152/41579.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Berning, Andrew Walter J. Verification of successive convexification algorithm. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41579

Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

8.
Park, Dohyung.
Efficient non-*convex* algorithms for large-scale learning problems.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/46581

► The emergence of modern large-scale datasets has led to a huge interest in the problem of learning hidden complex structures. Not only can models from…
(more)

Subjects/Keywords: Machine learning; Non-convex optimization

Record Details Similar Records

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APA (6^{th} Edition):

Park, D. (2016). Efficient non-convex algorithms for large-scale learning problems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46581

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Park, Dohyung. “Efficient non-convex algorithms for large-scale learning problems.” 2016. Thesis, University of Texas – Austin. Accessed December 18, 2018. http://hdl.handle.net/2152/46581.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Park, Dohyung. “Efficient non-convex algorithms for large-scale learning problems.” 2016. Web. 18 Dec 2018.

Vancouver:

Park D. Efficient non-convex algorithms for large-scale learning problems. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2152/46581.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Park D. Efficient non-convex algorithms for large-scale learning problems. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46581

Not specified: Masters Thesis or Doctoral Dissertation

University of Southern California

9. Taghavi, Soraya. Quantum computation and optimized error correction.

Degree: PhD, Electrical Engineering, 2010, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/308762/rec/5355

► Two subjects in the area of quantum computation are considered here. In the first chapter I present a universal model for a quantum Robot. Chapters…
(more)

Subjects/Keywords: quantum error correction; convex optimization

Record Details Similar Records

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APA (6^{th} Edition):

Taghavi, S. (2010). Quantum computation and optimized error correction. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/308762/rec/5355

Chicago Manual of Style (16^{th} Edition):

Taghavi, Soraya. “Quantum computation and optimized error correction.” 2010. Doctoral Dissertation, University of Southern California. Accessed December 18, 2018. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/308762/rec/5355.

MLA Handbook (7^{th} Edition):

Taghavi, Soraya. “Quantum computation and optimized error correction.” 2010. Web. 18 Dec 2018.

Vancouver:

Taghavi S. Quantum computation and optimized error correction. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2018 Dec 18]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/308762/rec/5355.

Council of Science Editors:

Taghavi S. Quantum computation and optimized error correction. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/308762/rec/5355

University of Ontario Institute of Technology

10.
Takeva-Velkova, Viliyana.
* Optimization* algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI).

Degree: 2010, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/104

► Magnetic Resonance Imaging (MRI) is an essential instrument in clinical diag- nosis; however, it is burdened by a slow data acquisition process due to physical…
(more)

Subjects/Keywords: Compressive sensing; Sparse MRI; Convex optimization

Record Details Similar Records

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APA (6^{th} Edition):

Takeva-Velkova, V. (2010). Optimization algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI). (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/104

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Takeva-Velkova, Viliyana. “Optimization algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI).” 2010. Thesis, University of Ontario Institute of Technology. Accessed December 18, 2018. http://hdl.handle.net/10155/104.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Takeva-Velkova, Viliyana. “Optimization algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI).” 2010. Web. 18 Dec 2018.

Vancouver:

Takeva-Velkova V. Optimization algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI). [Internet] [Thesis]. University of Ontario Institute of Technology; 2010. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/10155/104.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Takeva-Velkova V. Optimization algorithms in compressive sensing (CS) sparse magnetic resonance imaging (MRI). [Thesis]. University of Ontario Institute of Technology; 2010. Available from: http://hdl.handle.net/10155/104

Not specified: Masters Thesis or Doctoral Dissertation

11.
Umenberger, Jack.
* Convex* Identifcation of Stable Dynamical Systems
.

Degree: 2017, University of Sydney

URL: http://hdl.handle.net/2123/17321

► This thesis concerns the scalable application of *convex* *optimization* to data-driven modeling of dynamical systems, termed system identi cation in the control community. Two problems…
(more)

Subjects/Keywords: system identification; convex optimization; positive systems

Record Details Similar Records

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APA (6^{th} Edition):

Umenberger, J. (2017). Convex Identifcation of Stable Dynamical Systems . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/17321

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Umenberger, Jack. “Convex Identifcation of Stable Dynamical Systems .” 2017. Thesis, University of Sydney. Accessed December 18, 2018. http://hdl.handle.net/2123/17321.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Umenberger, Jack. “Convex Identifcation of Stable Dynamical Systems .” 2017. Web. 18 Dec 2018.

Vancouver:

Umenberger J. Convex Identifcation of Stable Dynamical Systems . [Internet] [Thesis]. University of Sydney; 2017. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2123/17321.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Umenberger J. Convex Identifcation of Stable Dynamical Systems . [Thesis]. University of Sydney; 2017. Available from: http://hdl.handle.net/2123/17321

Not specified: Masters Thesis or Doctoral Dissertation

University of Ghana

12.
Katsekpor, T.
Iterative Methods for Large Scale *Convex* * Optimization*
.

Degree: 2017, University of Ghana

URL: http://ugspace.ug.edu.gh/handle/123456789/23393

► This thesis presents a detailed description and analysis of Bregman’s iterative method for *convex* programming with linear constraints. Row and block action methods for large…
(more)

Subjects/Keywords: Iterative Methods; Large Scale Convex; Optimization

Record Details Similar Records

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

APA (6^{th} Edition):

Katsekpor, T. (2017). Iterative Methods for Large Scale Convex Optimization . (Doctoral Dissertation). University of Ghana. Retrieved from http://ugspace.ug.edu.gh/handle/123456789/23393

Chicago Manual of Style (16^{th} Edition):

Katsekpor, T. “Iterative Methods for Large Scale Convex Optimization .” 2017. Doctoral Dissertation, University of Ghana. Accessed December 18, 2018. http://ugspace.ug.edu.gh/handle/123456789/23393.

MLA Handbook (7^{th} Edition):

Katsekpor, T. “Iterative Methods for Large Scale Convex Optimization .” 2017. Web. 18 Dec 2018.

Vancouver:

Katsekpor T. Iterative Methods for Large Scale Convex Optimization . [Internet] [Doctoral dissertation]. University of Ghana; 2017. [cited 2018 Dec 18]. Available from: http://ugspace.ug.edu.gh/handle/123456789/23393.

Council of Science Editors:

Katsekpor T. Iterative Methods for Large Scale Convex Optimization . [Doctoral Dissertation]. University of Ghana; 2017. Available from: http://ugspace.ug.edu.gh/handle/123456789/23393

Universidade Nova

13. Soares, Diogo Lopes. Design of multidimensional compact constellations with high power efficiency.

Degree: 2013, Universidade Nova

URL: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11111

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
*Advisors/Committee Members: Dinis, Rui, Beko, Marko.*

Subjects/Keywords: Multidimensional constellations; Power efficiency; Convex optimization

Record Details Similar Records

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APA (6^{th} Edition):

Soares, D. L. (2013). Design of multidimensional compact constellations with high power efficiency. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11111

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Soares, Diogo Lopes. “Design of multidimensional compact constellations with high power efficiency.” 2013. Thesis, Universidade Nova. Accessed December 18, 2018. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11111.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Soares, Diogo Lopes. “Design of multidimensional compact constellations with high power efficiency.” 2013. Web. 18 Dec 2018.

Vancouver:

Soares DL. Design of multidimensional compact constellations with high power efficiency. [Internet] [Thesis]. Universidade Nova; 2013. [cited 2018 Dec 18]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11111.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Soares DL. Design of multidimensional compact constellations with high power efficiency. [Thesis]. Universidade Nova; 2013. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11111

Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

14.
Karimi, Mehdi.
*Convex**Optimization* via Domain-Driven Barriers and Primal-Dual Interior-Point Methods.

Degree: 2017, University of Waterloo

URL: http://hdl.handle.net/10012/12209

► This thesis studies the theory and implementation of infeasible-start primal-dual interior-point methods for *convex* *optimization* problems. *Convex* *optimization* has applications in many fields of engineering…
(more)

Subjects/Keywords: convex optimization; primal-dual interior-point methods

Record Details Similar Records

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APA (6^{th} Edition):

Karimi, M. (2017). Convex Optimization via Domain-Driven Barriers and Primal-Dual Interior-Point Methods. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12209

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Karimi, Mehdi. “Convex Optimization via Domain-Driven Barriers and Primal-Dual Interior-Point Methods.” 2017. Thesis, University of Waterloo. Accessed December 18, 2018. http://hdl.handle.net/10012/12209.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Karimi, Mehdi. “Convex Optimization via Domain-Driven Barriers and Primal-Dual Interior-Point Methods.” 2017. Web. 18 Dec 2018.

Vancouver:

Karimi M. Convex Optimization via Domain-Driven Barriers and Primal-Dual Interior-Point Methods. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/10012/12209.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Karimi M. Convex Optimization via Domain-Driven Barriers and Primal-Dual Interior-Point Methods. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12209

Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

15.
Zhang, H.M.
Distributed *Convex* *Optimization*: A Study on the Primal-Dual Method of Multipliers:.

Degree: 2015, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Zhang, H M. “Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers:.” 2015. Masters Thesis, Delft University of Technology. Accessed December 18, 2018. http://resolver.tudelft.nl/uuid:932db0bb-da4c-4ffe-892a-036d01a8071b.

MLA Handbook (7^{th} Edition):

Zhang, H M. “Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers:.” 2015. Web. 18 Dec 2018.

Vancouver:

Zhang HM. Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers:. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2018 Dec 18]. 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

Iowa State University

16. Li, Chong. Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds.

Degree: 2013, Iowa State University

URL: https://lib.dr.iastate.edu/etd/13421

► Since the success of obtaining the capacity (i.e. the maximal achievable transmission rate under which the message can be recovered with arbitrarily small probability of…
(more)

Subjects/Keywords: Capacity; Convex Optimization; Feedback; Information Theory; Engineering

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

APA (6^{th} Edition):

Li, C. (2013). Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/13421

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Li, Chong. “Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds.” 2013. Thesis, Iowa State University. Accessed December 18, 2018. https://lib.dr.iastate.edu/etd/13421.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Li, Chong. “Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds.” 2013. Web. 18 Dec 2018.

Vancouver:

Li C. Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds. [Internet] [Thesis]. Iowa State University; 2013. [cited 2018 Dec 18]. Available from: https://lib.dr.iastate.edu/etd/13421.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li C. Fundamental limitations on communication channels with noisy feedback: information flow, capacity and bounds. [Thesis]. Iowa State University; 2013. Available from: https://lib.dr.iastate.edu/etd/13421

Not specified: Masters Thesis or Doctoral Dissertation

Université Catholique de Louvain

17. Orban de Xivry, François-Xavier. Nearest stable system.

Degree: 2013, Université Catholique de Louvain

URL: http://hdl.handle.net/2078.1/132586

►

Stability is a universal concept which we experience in our everyday lives. It plays a central role in the study of dynamical systems and is… (more)

Subjects/Keywords: Stability; Dynamical system; Convex optimization; Nonconvex; Nonsmooth

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APA (6^{th} Edition):

Orban de Xivry, F. (2013). Nearest stable system. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/132586

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Orban de Xivry, François-Xavier. “Nearest stable system.” 2013. Thesis, Université Catholique de Louvain. Accessed December 18, 2018. http://hdl.handle.net/2078.1/132586.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Orban de Xivry, François-Xavier. “Nearest stable system.” 2013. Web. 18 Dec 2018.

Vancouver:

Orban de Xivry F. Nearest stable system. [Internet] [Thesis]. Université Catholique de Louvain; 2013. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2078.1/132586.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Orban de Xivry F. Nearest stable system. [Thesis]. Université Catholique de Louvain; 2013. Available from: http://hdl.handle.net/2078.1/132586

Not specified: Masters Thesis or Doctoral Dissertation

Tartu University

18.
Makkeh, Abdullah.
Applications of *optimization* in some complex systems
.

Degree: 2018, Tartu University

URL: http://hdl.handle.net/10062/61143

► Matemaatiline optimeerimine on optimeerimisülesandele optimaalse lahendi leidmine, see tähendab, et leitakse reaalarvuliste väärtustega funktsiooni (eesmärkfunktsiooni) teatud kitsendusi rahuldav maksimaalne või minimaalne väärtus. Matemaatiline optimeerimine on…
(more)

Subjects/Keywords: complex systems; optimization; convex sets; software

Record Details Similar Records

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

APA (6^{th} Edition):

Makkeh, A. (2018). Applications of optimization in some complex systems . (Thesis). Tartu University. Retrieved from http://hdl.handle.net/10062/61143

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Makkeh, Abdullah. “Applications of optimization in some complex systems .” 2018. Thesis, Tartu University. Accessed December 18, 2018. http://hdl.handle.net/10062/61143.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Makkeh, Abdullah. “Applications of optimization in some complex systems .” 2018. Web. 18 Dec 2018.

Vancouver:

Makkeh A. Applications of optimization in some complex systems . [Internet] [Thesis]. Tartu University; 2018. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/10062/61143.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Makkeh A. Applications of optimization in some complex systems . [Thesis]. Tartu University; 2018. Available from: http://hdl.handle.net/10062/61143

Not specified: Masters Thesis or Doctoral Dissertation

University of Minnesota

19.
Choi, Hyungjin.
Quantication of the Impact of Uncertainty in Power Systems using *Convex* * Optimization*.

Degree: PhD, Electrical Engineering, 2017, University of Minnesota

URL: http://hdl.handle.net/11299/190457

► Rampant integration of renewable resources (e.g., photovoltaic and wind-energy conversion systems) and uncontrollable and elastic loads (e.g., plug-in hybrid electric vehicles) are rapidly transforming power…
(more)

Subjects/Keywords: Convex Optimization; Power Systems; Sensitivity; Stability; Uncertainty

Record Details Similar Records

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APA (6^{th} Edition):

Choi, H. (2017). Quantication of the Impact of Uncertainty in Power Systems using Convex Optimization. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/190457

Chicago Manual of Style (16^{th} Edition):

Choi, Hyungjin. “Quantication of the Impact of Uncertainty in Power Systems using Convex Optimization.” 2017. Doctoral Dissertation, University of Minnesota. Accessed December 18, 2018. http://hdl.handle.net/11299/190457.

MLA Handbook (7^{th} Edition):

Choi, Hyungjin. “Quantication of the Impact of Uncertainty in Power Systems using Convex Optimization.” 2017. Web. 18 Dec 2018.

Vancouver:

Choi H. Quantication of the Impact of Uncertainty in Power Systems using Convex Optimization. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/11299/190457.

Council of Science Editors:

Choi H. Quantication of the Impact of Uncertainty in Power Systems using Convex Optimization. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/190457

Loughborough University

20.
Rossetti, Gaia.
Mathematical *optimization* techniques for cognitive radar networks.

Degree: PhD, 2018, Loughborough University

URL: https://dspace.lboro.ac.uk/2134/33419 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

► This thesis discusses mathematical *optimization* techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from…
(more)

Subjects/Keywords: Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

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APA (6^{th} Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/33419 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

Chicago Manual of Style (16^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Doctoral Dissertation, Loughborough University. Accessed December 18, 2018. https://dspace.lboro.ac.uk/2134/33419 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

MLA Handbook (7^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 18 Dec 2018.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2018 Dec 18]. Available from: https://dspace.lboro.ac.uk/2134/33419 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Doctoral Dissertation]. Loughborough University; 2018. Available from: https://dspace.lboro.ac.uk/2134/33419 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

Georgia Tech

21.
Lan, Guanghui.
*Convex**optimization* under inexact first-order information.

Degree: PhD, Industrial and Systems Engineering, 2009, Georgia Tech

URL: http://hdl.handle.net/1853/29732

► In this thesis we investigate the design and complexity analysis of the algorithms to solve *convex* programming problems under inexact first-order information. In the first…
(more)

Subjects/Keywords: Convex optimization; Stochastic programming; First-order methods; Uncertainty; Mathematical optimization; Convex functions; First-order logic

Record Details Similar Records

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

APA (6^{th} Edition):

Lan, G. (2009). Convex optimization under inexact first-order information. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29732

Chicago Manual of Style (16^{th} Edition):

Lan, Guanghui. “Convex optimization under inexact first-order information.” 2009. Doctoral Dissertation, Georgia Tech. Accessed December 18, 2018. http://hdl.handle.net/1853/29732.

MLA Handbook (7^{th} Edition):

Lan, Guanghui. “Convex optimization under inexact first-order information.” 2009. Web. 18 Dec 2018.

Vancouver:

Lan G. Convex optimization under inexact first-order information. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/1853/29732.

Council of Science Editors:

Lan G. Convex optimization under inexact first-order information. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29732

University of Oxford

22.
Banjac, Goran.
Operator splitting methods for *convex* *optimization* : analysis and implementation.

Degree: PhD, 2018, University of Oxford

URL: https://ora.ox.ac.uk/objects/uuid:17ac73af-9fdf-4cf6-a946-3048da3fc9c2 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740972

► *Convex* *optimization* problems are a class of mathematical problems which arise in numerous applications. Although interior-point methods can in principle solve these problems efficiently, they…
(more)

Subjects/Keywords: Mathematical optimization; Convex optimization; Operator splitting methods; Infeasibility detection; Linear convergence

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

APA (6^{th} Edition):

Banjac, G. (2018). Operator splitting methods for convex optimization : analysis and implementation. (Doctoral Dissertation). University of Oxford. Retrieved from https://ora.ox.ac.uk/objects/uuid:17ac73af-9fdf-4cf6-a946-3048da3fc9c2 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740972

Chicago Manual of Style (16^{th} Edition):

Banjac, Goran. “Operator splitting methods for convex optimization : analysis and implementation.” 2018. Doctoral Dissertation, University of Oxford. Accessed December 18, 2018. https://ora.ox.ac.uk/objects/uuid:17ac73af-9fdf-4cf6-a946-3048da3fc9c2 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740972.

MLA Handbook (7^{th} Edition):

Banjac, Goran. “Operator splitting methods for convex optimization : analysis and implementation.” 2018. Web. 18 Dec 2018.

Vancouver:

Banjac G. Operator splitting methods for convex optimization : analysis and implementation. [Internet] [Doctoral dissertation]. University of Oxford; 2018. [cited 2018 Dec 18]. Available from: https://ora.ox.ac.uk/objects/uuid:17ac73af-9fdf-4cf6-a946-3048da3fc9c2 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740972.

Council of Science Editors:

Banjac G. Operator splitting methods for convex optimization : analysis and implementation. [Doctoral Dissertation]. University of Oxford; 2018. Available from: https://ora.ox.ac.uk/objects/uuid:17ac73af-9fdf-4cf6-a946-3048da3fc9c2 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740972

Penn State University

23. Kang, Bosung. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).

Degree: PhD, Electrical Engineering, 2015, Penn State University

URL: https://etda.libraries.psu.edu/catalog/26539

► Estimating the disturbance or clutter covariance is a centrally important problem in radar space time adaptive processing (STAP) since estimation of the disturbance or interference…
(more)

Subjects/Keywords: convex optimization; STAP; radar signal processing; constrained optimization; detection and estimation

Record Details Similar Records

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

APA (6^{th} Edition):

Kang, B. (2015). Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26539

Chicago Manual of Style (16^{th} Edition):

Kang, Bosung. “Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).” 2015. Doctoral Dissertation, Penn State University. Accessed December 18, 2018. https://etda.libraries.psu.edu/catalog/26539.

MLA Handbook (7^{th} Edition):

Kang, Bosung. “Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).” 2015. Web. 18 Dec 2018.

Vancouver:

Kang B. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2018 Dec 18]. Available from: https://etda.libraries.psu.edu/catalog/26539.

Council of Science Editors:

Kang B. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26539

Lehigh University

24.
Kuang, Xiaolong.
Conic Programming Approaches for Polynomial *Optimization*: Theory and Applications.

Degree: PhD, Industrial Engineering, 2017, Lehigh University

URL: https://preserve.lehigh.edu/etd/2952

► Historically, polynomials are among the most popular class of functions used for empirical modeling in science and engineering. Polynomials are easy to evaluate, appear naturally…
(more)

Subjects/Keywords: Conic Programming; Convex Optimization; Polynomial Optimization; Industrial Engineering

Record Details Similar Records

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

APA (6^{th} Edition):

Kuang, X. (2017). Conic Programming Approaches for Polynomial Optimization: Theory and Applications. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/2952

Chicago Manual of Style (16^{th} Edition):

Kuang, Xiaolong. “Conic Programming Approaches for Polynomial Optimization: Theory and Applications.” 2017. Doctoral Dissertation, Lehigh University. Accessed December 18, 2018. https://preserve.lehigh.edu/etd/2952.

MLA Handbook (7^{th} Edition):

Kuang, Xiaolong. “Conic Programming Approaches for Polynomial Optimization: Theory and Applications.” 2017. Web. 18 Dec 2018.

Vancouver:

Kuang X. Conic Programming Approaches for Polynomial Optimization: Theory and Applications. [Internet] [Doctoral dissertation]. Lehigh University; 2017. [cited 2018 Dec 18]. Available from: https://preserve.lehigh.edu/etd/2952.

Council of Science Editors:

Kuang X. Conic Programming Approaches for Polynomial Optimization: Theory and Applications. [Doctoral Dissertation]. Lehigh University; 2017. Available from: https://preserve.lehigh.edu/etd/2952

University of California – Berkeley

25.
Godwin, Mark Franklin.
Quasi-Newton Algorithms for Non-smooth Online Strongly *Convex* * Optimization*.

Degree: Mechanical Engineering, 2011, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/7fw187gd

► The growing prevalence of networked systems with local sensing and computational capability will result in an increasing array of online and large scale *optimization* problems.…
(more)

Subjects/Keywords: Electrical engineering; Mechanical engineering; Computer science; online convex optimization; quasi-Newton; strongly convex

Record Details Similar Records

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

APA (6^{th} Edition):

Godwin, M. F. (2011). Quasi-Newton Algorithms for Non-smooth Online Strongly Convex Optimization. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/7fw187gd

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Godwin, Mark Franklin. “Quasi-Newton Algorithms for Non-smooth Online Strongly Convex Optimization.” 2011. Thesis, University of California – Berkeley. Accessed December 18, 2018. http://www.escholarship.org/uc/item/7fw187gd.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Godwin, Mark Franklin. “Quasi-Newton Algorithms for Non-smooth Online Strongly Convex Optimization.” 2011. Web. 18 Dec 2018.

Vancouver:

Godwin MF. Quasi-Newton Algorithms for Non-smooth Online Strongly Convex Optimization. [Internet] [Thesis]. University of California – Berkeley; 2011. [cited 2018 Dec 18]. Available from: http://www.escholarship.org/uc/item/7fw187gd.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Godwin MF. Quasi-Newton Algorithms for Non-smooth Online Strongly Convex Optimization. [Thesis]. University of California – Berkeley; 2011. Available from: http://www.escholarship.org/uc/item/7fw187gd

Not specified: Masters Thesis or Doctoral Dissertation

Université Catholique de Louvain

26.
Taylor, Adrien.
* Convex* interpolation and performance estimation of first-order methods for

Degree: 2017, Université Catholique de Louvain

URL: http://hdl.handle.net/2078.1/182881

►

The goal of this thesis is to show how to derive in a completely automated way exact and global worst-case guarantees for first-order methods in… (more)

Subjects/Keywords: Convex optimization; Convex analysis; First-order methods; Worst-case analysis; Semidefinite programming; Performance Estimation; Steepest descent; Convex interpolation

Record Details Similar Records

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

APA (6^{th} Edition):

Taylor, A. (2017). Convex interpolation and performance estimation of first-order methods for convex optimization. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/182881

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Taylor, Adrien. “Convex interpolation and performance estimation of first-order methods for convex optimization.” 2017. Thesis, Université Catholique de Louvain. Accessed December 18, 2018. http://hdl.handle.net/2078.1/182881.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Taylor, Adrien. “Convex interpolation and performance estimation of first-order methods for convex optimization.” 2017. Web. 18 Dec 2018.

Vancouver:

Taylor A. Convex interpolation and performance estimation of first-order methods for convex optimization. [Internet] [Thesis]. Université Catholique de Louvain; 2017. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/2078.1/182881.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Taylor A. Convex interpolation and performance estimation of first-order methods for convex optimization. [Thesis]. Université Catholique de Louvain; 2017. Available from: http://hdl.handle.net/2078.1/182881

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

27.
Ahmadi, Hesamoddin.
On the Analysis of Data-driven and Distributed Algorithms
for *Convex* *Optimization* Problems.

Degree: PhD, Industrial Engineering, 2016, Penn State University

URL: https://etda.libraries.psu.edu/catalog/29502

► 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

Record Details Similar Records

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APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Doctoral Dissertation, Penn State University. Accessed December 18, 2018. https://etda.libraries.psu.edu/catalog/29502.

MLA Handbook (7^{th} Edition):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Web. 18 Dec 2018.

Vancouver:

Ahmadi H. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. [Internet] [Doctoral dissertation]. Penn State University; 2016. [cited 2018 Dec 18]. Available from: https://etda.libraries.psu.edu/catalog/29502.

Council of Science Editors:

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

Carnegie Mellon University

28. Xiong, Xuehan. Supervised Descent Method.

Degree: 2015, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/652

► In this dissertation, we focus on solving Nonlinear Least Squares problems using a supervised approach. In particular, we developed a Supervised Descent Method (SDM), performed…
(more)

Subjects/Keywords: nonlinear optimization; global optimization; non-convex optimization; nonlinear least squares; face alignment; facial feature tracking

Record Details Similar Records

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APA (6^{th} Edition):

Xiong, X. (2015). Supervised Descent Method. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/652

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Xiong, Xuehan. “Supervised Descent Method.” 2015. Thesis, Carnegie Mellon University. Accessed December 18, 2018. http://repository.cmu.edu/dissertations/652.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Xiong, Xuehan. “Supervised Descent Method.” 2015. Web. 18 Dec 2018.

Vancouver:

Xiong X. Supervised Descent Method. [Internet] [Thesis]. Carnegie Mellon University; 2015. [cited 2018 Dec 18]. Available from: http://repository.cmu.edu/dissertations/652.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xiong X. Supervised Descent Method. [Thesis]. Carnegie Mellon University; 2015. Available from: http://repository.cmu.edu/dissertations/652

Not specified: Masters Thesis or Doctoral Dissertation

University of Western Ontario

29. Baxter, John SH. Contributions of Continuous Max-Flow Theory to Medical Image Processing.

Degree: 2017, University of Western Ontario

URL: https://ir.lib.uwo.ca/etd/4602

► Discrete graph cuts and continuous max-flow theory have created a paradigm shift in many areas of medical image processing. As previous methods limited themselves to…
(more)

Subjects/Keywords: optimization-based segmentation; image enhancement; variational optimization; convex optimization; Biomedical Engineering and Bioengineering

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APA (6^{th} Edition):

Baxter, J. S. (2017). Contributions of Continuous Max-Flow Theory to Medical Image Processing. (Thesis). University of Western Ontario. Retrieved from https://ir.lib.uwo.ca/etd/4602

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Baxter, John SH. “Contributions of Continuous Max-Flow Theory to Medical Image Processing.” 2017. Thesis, University of Western Ontario. Accessed December 18, 2018. https://ir.lib.uwo.ca/etd/4602.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Baxter, John SH. “Contributions of Continuous Max-Flow Theory to Medical Image Processing.” 2017. Web. 18 Dec 2018.

Vancouver:

Baxter JS. Contributions of Continuous Max-Flow Theory to Medical Image Processing. [Internet] [Thesis]. University of Western Ontario; 2017. [cited 2018 Dec 18]. Available from: https://ir.lib.uwo.ca/etd/4602.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Baxter JS. Contributions of Continuous Max-Flow Theory to Medical Image Processing. [Thesis]. University of Western Ontario; 2017. Available from: https://ir.lib.uwo.ca/etd/4602

Not specified: Masters Thesis or Doctoral Dissertation

University of Minnesota

30. Devulapalli, Raghuveer. Geometric partitioning algorithms for fair division of geographic resources.

Degree: PhD, Industrial and Systems Engineering, 2014, University of Minnesota

URL: http://hdl.handle.net/11299/165305

► This dissertation focuses on a fundamental but under-researched problem: how does one divide a piece of territory into smaller pieces in an efficient way? In…
(more)

Subjects/Keywords: Computational Geometry; Convex Optimization; Geometric Algorithms; Geometric Optimization; Infinite Dimensional Optimization; Operations Research

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APA (6^{th} Edition):

Devulapalli, R. (2014). Geometric partitioning algorithms for fair division of geographic resources. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/165305

Chicago Manual of Style (16^{th} Edition):

Devulapalli, Raghuveer. “Geometric partitioning algorithms for fair division of geographic resources.” 2014. Doctoral Dissertation, University of Minnesota. Accessed December 18, 2018. http://hdl.handle.net/11299/165305.

MLA Handbook (7^{th} Edition):

Devulapalli, Raghuveer. “Geometric partitioning algorithms for fair division of geographic resources.” 2014. Web. 18 Dec 2018.

Vancouver:

Devulapalli R. Geometric partitioning algorithms for fair division of geographic resources. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2018 Dec 18]. Available from: http://hdl.handle.net/11299/165305.

Council of Science Editors:

Devulapalli R. Geometric partitioning algorithms for fair division of geographic resources. [Doctoral Dissertation]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/165305