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1.
Collonge, Julien.
Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective *Optimization* : Theoretical Results and Algorithms.

Degree: Docteur es, Mathématiques appliquées, 2014, Nouvelle Calédonie

URL: http://www.theses.fr/2014NCAL0061

►

Cette thèse relate certains aspects liés à l'analyse post-Pareto issue de Problèmes d'Optimisation Vectorielle Stochastique. Un problème d'optimisation Vectorielle Stochastique consiste à optimiser l'espérance d'une… (more)

Subjects/Keywords: Optimisation vectorielle; Optimisation stochastique; Analyse post Pareto; Optimization over a Pareto set; Deterministic Vector Optimization; Convex Vector Optimization; 519

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

APA (6^{th} Edition):

Collonge, J. (2014). Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective Optimization : Theoretical Results and Algorithms. (Doctoral Dissertation). Nouvelle Calédonie. Retrieved from http://www.theses.fr/2014NCAL0061

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

Collonge, Julien. “Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective Optimization : Theoretical Results and Algorithms.” 2014. Doctoral Dissertation, Nouvelle Calédonie. Accessed May 24, 2018. http://www.theses.fr/2014NCAL0061.

MLA Handbook (7^{th} Edition):

Collonge, Julien. “Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective Optimization : Theoretical Results and Algorithms.” 2014. Web. 24 May 2018.

Vancouver:

Collonge J. Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective Optimization : Theoretical Results and Algorithms. [Internet] [Doctoral dissertation]. Nouvelle Calédonie; 2014. [cited 2018 May 24]. Available from: http://www.theses.fr/2014NCAL0061.

Council of Science Editors:

Collonge J. Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes. : Post-Pareto Analysis in Stochastic Multi-Objective Optimization : Theoretical Results and Algorithms. [Doctoral Dissertation]. Nouvelle Calédonie; 2014. Available from: http://www.theses.fr/2014NCAL0061

2.
Kim, Gitae.
Solving
support *vector* machine classification problems and their
applications to supplier selection.

Degree: PhD, Department of Industrial & Manufacturing Systems Engineering, 2011, Kansas State University

URL: http://hdl.handle.net/2097/8719

► Recently, interdisciplinary (management, engineering, science, and economics) collaboration research has been growing to achieve the synergy and to reinforce the weakness of each discipline. Along…
(more)

Subjects/Keywords: Support Vector Machine; Nonlinear Knapsack Problem; Supplier Selection; Convex Optimization; Supply Chain Management; Classification; Engineering (0537)

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

APA (6^{th} Edition):

Kim, G. (2011). Solving support vector machine classification problems and their applications to supplier selection. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/8719

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

Kim, Gitae. “Solving support vector machine classification problems and their applications to supplier selection.” 2011. Doctoral Dissertation, Kansas State University. Accessed May 24, 2018. http://hdl.handle.net/2097/8719.

MLA Handbook (7^{th} Edition):

Kim, Gitae. “Solving support vector machine classification problems and their applications to supplier selection.” 2011. Web. 24 May 2018.

Vancouver:

Kim G. Solving support vector machine classification problems and their applications to supplier selection. [Internet] [Doctoral dissertation]. Kansas State University; 2011. [cited 2018 May 24]. Available from: http://hdl.handle.net/2097/8719.

Council of Science Editors:

Kim G. Solving support vector machine classification problems and their applications to supplier selection. [Doctoral Dissertation]. Kansas State University; 2011. Available from: http://hdl.handle.net/2097/8719

3.
Ulus, Firdevs.
Algorithms for *Vector* *Optimization* Problems
.

Degree: PhD, 2015, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp01n009w461x

► This dissertation studies algorithms to solve linear and *convex* *vector* *optimization* problems. A parametric simplex algorithm for solving linear *vector* *optimization* problems (LVOPs) and two…
(more)

Subjects/Keywords: Algorithms; Convex Programming; Duality; Linear Programming; Multiobjective optimization; Vector optimization

…1
1.2
*Convex* *Vector* *Optimization* . . . . . . . . . . . . . . . . . . . . . . . . . .
5… …53
4 *Convex* *Vector* *Optimization* Problems
58
4.1
Problem Setting and Solution Concepts… …*vector* *optimization* problems
(LVOPs) and *convex* *vector* *optimization* problems (… …solving an LP or performing
a Phase 1 algorithm.
1.2
*Convex* *Vector* *Optimization*
*Convex* *vector*… …*convex* analysis are presented, the linear *vector* *optimization* problem and the solution
concepts…

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

APA (6^{th} Edition):

Ulus, F. (2015). Algorithms for Vector Optimization Problems . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01n009w461x

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

Ulus, Firdevs. “Algorithms for Vector Optimization Problems .” 2015. Doctoral Dissertation, Princeton University. Accessed May 24, 2018. http://arks.princeton.edu/ark:/88435/dsp01n009w461x.

MLA Handbook (7^{th} Edition):

Ulus, Firdevs. “Algorithms for Vector Optimization Problems .” 2015. Web. 24 May 2018.

Vancouver:

Ulus F. Algorithms for Vector Optimization Problems . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2018 May 24]. Available from: http://arks.princeton.edu/ark:/88435/dsp01n009w461x.

Council of Science Editors:

Ulus F. Algorithms for Vector Optimization Problems . [Doctoral Dissertation]. Princeton University; 2015. Available from: http://arks.princeton.edu/ark:/88435/dsp01n009w461x

4.
Cox, Bruce.
Applications of accuracy certificates for problems with *convex* structure.

Degree: PhD, Industrial and Systems Engineering, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/39489

► Applications of accuracy certificates for problems with *convex* structure This dissertation addresses the efficient generation and potential applications of accuracy certificates in the framework…
(more)

Subjects/Keywords: Accuracy certificates; Convex optimization; Vector algebra; Linear programming; Convex functions; Convex domains

…of accuracy
certificates in the framework of “black-box-represented” *convex* *optimization*… …certificates
for black-box-represented *convex* *optimization*. In the second part, we extend the toolbox… …of black-box-oriented *convex* *optimization* algorithms with accuracy certificates by… …*convex*-concave saddle point problem gives rise to a primal-dual pair of *convex* *optimization*… …identifications; e.g., the *vector* field and the accuracy measure associated
with a *convex*-concave saddle…

Record Details Similar Records

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

APA (6^{th} Edition):

Cox, B. (2011). Applications of accuracy certificates for problems with convex structure. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/39489

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

Cox, Bruce. “Applications of accuracy certificates for problems with convex structure.” 2011. Doctoral Dissertation, Georgia Tech. Accessed May 24, 2018. http://hdl.handle.net/1853/39489.

MLA Handbook (7^{th} Edition):

Cox, Bruce. “Applications of accuracy certificates for problems with convex structure.” 2011. Web. 24 May 2018.

Vancouver:

Cox B. Applications of accuracy certificates for problems with convex structure. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2018 May 24]. Available from: http://hdl.handle.net/1853/39489.

Council of Science Editors:

Cox B. Applications of accuracy certificates for problems with convex structure. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/39489

Colorado State University

5.
Rohrbacker, Nicholas.
Sparse multivariate analyses via ℓ1-regularized *optimization* problems solved with Bregman Iterative Techniques.

Degree: PhD, Mathematics, 2007, Colorado State University

URL: http://hdl.handle.net/10217/71581

► In this dissertation we propose Split Bregman algorithms for several multivariate analytic techniques for dimensionality reduction and feature selection including Sparse Principal Components Analysis, Bisparse…
(more)

Subjects/Keywords: convex optimization; modularity; sparse PCA; Bisparse Singular Value Decomposition; Split Bregman; support vector machine

Record Details Similar Records

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

APA (6^{th} Edition):

Rohrbacker, N. (2007). Sparse multivariate analyses via ℓ1-regularized optimization problems solved with Bregman Iterative Techniques. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/71581

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

Rohrbacker, Nicholas. “Sparse multivariate analyses via ℓ1-regularized optimization problems solved with Bregman Iterative Techniques.” 2007. Doctoral Dissertation, Colorado State University. Accessed May 24, 2018. http://hdl.handle.net/10217/71581.

MLA Handbook (7^{th} Edition):

Rohrbacker, Nicholas. “Sparse multivariate analyses via ℓ1-regularized optimization problems solved with Bregman Iterative Techniques.” 2007. Web. 24 May 2018.

Vancouver:

Rohrbacker N. Sparse multivariate analyses via ℓ1-regularized optimization problems solved with Bregman Iterative Techniques. [Internet] [Doctoral dissertation]. Colorado State University; 2007. [cited 2018 May 24]. Available from: http://hdl.handle.net/10217/71581.

Council of Science Editors:

Rohrbacker N. Sparse multivariate analyses via ℓ1-regularized optimization problems solved with Bregman Iterative Techniques. [Doctoral Dissertation]. Colorado State University; 2007. Available from: http://hdl.handle.net/10217/71581

6.
Sapankevych, Nicholas.
Constrained Motion Particle Swarm *Optimization* for Non-Linear Time Series Prediction.

Degree: 2015, University of South Florida

URL: http://scholarcommons.usf.edu/etd/5569

► Time series prediction techniques have been used in many real-world applications such as financial market prediction, electric utility load forecasting, weather and environmental state prediction,…
(more)

Subjects/Keywords: Competition for Artificial Time Series; Convex Optimization; EUNITE; Mackey-Glass; Support Vector Regression; Electrical and Computer Engineering

…1].
2.1.2 Support *Vector* Machines and Particle Swarm *Optimization*
As mentioned in the… …*optimization* problem that ensures the flatness criterion is met. A *convex* *optimization* problem
is… …SVR, we formulate a *convex* *optimization* problem with two linear constraints as
shown in… …Illustrating Support Vectors and Outliers
17
Figure 3.3
Support *Vector* Regression Linear… …Approximation Example
20
Figure 3.4
Support *Vector* Regression Non Linear Approximation Example
21…

Record Details Similar Records

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

APA (6^{th} Edition):

Sapankevych, N. (2015). Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction. (Thesis). University of South Florida. Retrieved from http://scholarcommons.usf.edu/etd/5569

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):

Sapankevych, Nicholas. “Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction.” 2015. Thesis, University of South Florida. Accessed May 24, 2018. http://scholarcommons.usf.edu/etd/5569.

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sapankevych, Nicholas. “Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction.” 2015. Web. 24 May 2018.

Vancouver:

Sapankevych N. Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction. [Internet] [Thesis]. University of South Florida; 2015. [cited 2018 May 24]. Available from: http://scholarcommons.usf.edu/etd/5569.

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

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sapankevych N. Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction. [Thesis]. University of South Florida; 2015. Available from: http://scholarcommons.usf.edu/etd/5569

Not specified: Masters Thesis or Doctoral Dissertation