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You searched for subject:(stochastic approximation). Showing records 1 – 30 of 209 total matches.

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University of Georgia

1. Zhuang, Chao. Stochastic approximation methods and applications in financial optimization problems.

Degree: PhD, Mathematics, 2008, University of Georgia

 Optimizations play an increasingly indispensable role in financial decisions and financial models. Many problems in mathematical finance, such as asset allocation, trading strategy, and derivative… (more)

Subjects/Keywords: Stochastic Approximation

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APA (6th Edition):

Zhuang, C. (2008). Stochastic approximation methods and applications in financial optimization problems. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/zhuang_chao_200808_phd

Chicago Manual of Style (16th Edition):

Zhuang, Chao. “Stochastic approximation methods and applications in financial optimization problems.” 2008. Doctoral Dissertation, University of Georgia. Accessed October 19, 2019. http://purl.galileo.usg.edu/uga_etd/zhuang_chao_200808_phd.

MLA Handbook (7th Edition):

Zhuang, Chao. “Stochastic approximation methods and applications in financial optimization problems.” 2008. Web. 19 Oct 2019.

Vancouver:

Zhuang C. Stochastic approximation methods and applications in financial optimization problems. [Internet] [Doctoral dissertation]. University of Georgia; 2008. [cited 2019 Oct 19]. Available from: http://purl.galileo.usg.edu/uga_etd/zhuang_chao_200808_phd.

Council of Science Editors:

Zhuang C. Stochastic approximation methods and applications in financial optimization problems. [Doctoral Dissertation]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/zhuang_chao_200808_phd


Texas A&M University

2. Cheng, Yichen. Stochastic Approximation and Its Application in MCMC.

Degree: 2013, Texas A&M University

Stochastic approximation has been widely used since first proposed by Herbert Robbins and Sutton Monro in 1951. It is an iterative stochastic method that attempts… (more)

Subjects/Keywords: stochastic approximation

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APA (6th Edition):

Cheng, Y. (2013). Stochastic Approximation and Its Application in MCMC. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151016

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):

Cheng, Yichen. “Stochastic Approximation and Its Application in MCMC.” 2013. Thesis, Texas A&M University. Accessed October 19, 2019. http://hdl.handle.net/1969.1/151016.

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

MLA Handbook (7th Edition):

Cheng, Yichen. “Stochastic Approximation and Its Application in MCMC.” 2013. Web. 19 Oct 2019.

Vancouver:

Cheng Y. Stochastic Approximation and Its Application in MCMC. [Internet] [Thesis]. Texas A&M University; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1969.1/151016.

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

Council of Science Editors:

Cheng Y. Stochastic Approximation and Its Application in MCMC. [Thesis]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151016

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


Michigan State University

3. Yuan, Chao. Uniform behavior of stochastic approximation methods.

Degree: PhD, Department of Statistics and Probability, 1996, Michigan State University

Subjects/Keywords: Stochastic approximation

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APA (6th Edition):

Yuan, C. (1996). Uniform behavior of stochastic approximation methods. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:29765

Chicago Manual of Style (16th Edition):

Yuan, Chao. “Uniform behavior of stochastic approximation methods.” 1996. Doctoral Dissertation, Michigan State University. Accessed October 19, 2019. http://etd.lib.msu.edu/islandora/object/etd:29765.

MLA Handbook (7th Edition):

Yuan, Chao. “Uniform behavior of stochastic approximation methods.” 1996. Web. 19 Oct 2019.

Vancouver:

Yuan C. Uniform behavior of stochastic approximation methods. [Internet] [Doctoral dissertation]. Michigan State University; 1996. [cited 2019 Oct 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:29765.

Council of Science Editors:

Yuan C. Uniform behavior of stochastic approximation methods. [Doctoral Dissertation]. Michigan State University; 1996. Available from: http://etd.lib.msu.edu/islandora/object/etd:29765


Penn State University

4. Kannan, Aswin. Distributed Algorithms for Optimization and.

Degree: PhD, Industrial Engineering, 2014, Penn State University

 This dissertation considers three sets of problems arising from optimization and game-theoretic problems complicated by the presence of uncertainty, limited information, and problem misspecification. Broadly… (more)

Subjects/Keywords: Variational inequalities; distributed algorithm; stochastic approximation; pseudomonotone.

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APA (6th Edition):

Kannan, A. (2014). Distributed Algorithms for Optimization and. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/24252

Chicago Manual of Style (16th Edition):

Kannan, Aswin. “Distributed Algorithms for Optimization and.” 2014. Doctoral Dissertation, Penn State University. Accessed October 19, 2019. https://etda.libraries.psu.edu/catalog/24252.

MLA Handbook (7th Edition):

Kannan, Aswin. “Distributed Algorithms for Optimization and.” 2014. Web. 19 Oct 2019.

Vancouver:

Kannan A. Distributed Algorithms for Optimization and. [Internet] [Doctoral dissertation]. Penn State University; 2014. [cited 2019 Oct 19]. Available from: https://etda.libraries.psu.edu/catalog/24252.

Council of Science Editors:

Kannan A. Distributed Algorithms for Optimization and. [Doctoral Dissertation]. Penn State University; 2014. Available from: https://etda.libraries.psu.edu/catalog/24252


University of Edinburgh

5. Schnoerr, David Benjamin. Approximation methods and inference for stochastic biochemical kinetics.

Degree: PhD, 2016, University of Edinburgh

 Recent experiments have shown the fundamental role that random fluctuations play in many chemical systems in living cells, such as gene regulatory networks. Mathematical models… (more)

Subjects/Keywords: 519.2; stochastic processes; approximation methods; statistical inference

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APA (6th Edition):

Schnoerr, D. B. (2016). Approximation methods and inference for stochastic biochemical kinetics. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/25444

Chicago Manual of Style (16th Edition):

Schnoerr, David Benjamin. “Approximation methods and inference for stochastic biochemical kinetics.” 2016. Doctoral Dissertation, University of Edinburgh. Accessed October 19, 2019. http://hdl.handle.net/1842/25444.

MLA Handbook (7th Edition):

Schnoerr, David Benjamin. “Approximation methods and inference for stochastic biochemical kinetics.” 2016. Web. 19 Oct 2019.

Vancouver:

Schnoerr DB. Approximation methods and inference for stochastic biochemical kinetics. [Internet] [Doctoral dissertation]. University of Edinburgh; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1842/25444.

Council of Science Editors:

Schnoerr DB. Approximation methods and inference for stochastic biochemical kinetics. [Doctoral Dissertation]. University of Edinburgh; 2016. Available from: http://hdl.handle.net/1842/25444


University of Arizona

6. Leach, Andrew Bradford. Monte Carlo Methods for Stochastic Differential Equations and their Applications .

Degree: 2017, University of Arizona

 We introduce computationally efficient Monte Carlo methods for studying the statistics of stochastic differential equations in two distinct settings. In the first, we derive importance… (more)

Subjects/Keywords: Continuation; Gaussian Approximation; Importance Sampling; Monte Carlo Methods; Stochastic Approximation; Stochastic Differential Equations

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APA (6th Edition):

Leach, A. B. (2017). Monte Carlo Methods for Stochastic Differential Equations and their Applications . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/624570

Chicago Manual of Style (16th Edition):

Leach, Andrew Bradford. “Monte Carlo Methods for Stochastic Differential Equations and their Applications .” 2017. Doctoral Dissertation, University of Arizona. Accessed October 19, 2019. http://hdl.handle.net/10150/624570.

MLA Handbook (7th Edition):

Leach, Andrew Bradford. “Monte Carlo Methods for Stochastic Differential Equations and their Applications .” 2017. Web. 19 Oct 2019.

Vancouver:

Leach AB. Monte Carlo Methods for Stochastic Differential Equations and their Applications . [Internet] [Doctoral dissertation]. University of Arizona; 2017. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10150/624570.

Council of Science Editors:

Leach AB. Monte Carlo Methods for Stochastic Differential Equations and their Applications . [Doctoral Dissertation]. University of Arizona; 2017. Available from: http://hdl.handle.net/10150/624570


Michigan State University

7. Ruppert, David, 1948-. A new dynamic stochastic approximation procedure.

Degree: PhD, 1977, Michigan State University

Subjects/Keywords: Stochastic approximation; Approximation theory

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APA (6th Edition):

Ruppert, David, 1. (1977). A new dynamic stochastic approximation procedure. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:43624

Chicago Manual of Style (16th Edition):

Ruppert, David, 1948-. “A new dynamic stochastic approximation procedure.” 1977. Doctoral Dissertation, Michigan State University. Accessed October 19, 2019. http://etd.lib.msu.edu/islandora/object/etd:43624.

MLA Handbook (7th Edition):

Ruppert, David, 1948-. “A new dynamic stochastic approximation procedure.” 1977. Web. 19 Oct 2019.

Vancouver:

Ruppert, David 1. A new dynamic stochastic approximation procedure. [Internet] [Doctoral dissertation]. Michigan State University; 1977. [cited 2019 Oct 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:43624.

Council of Science Editors:

Ruppert, David 1. A new dynamic stochastic approximation procedure. [Doctoral Dissertation]. Michigan State University; 1977. Available from: http://etd.lib.msu.edu/islandora/object/etd:43624


Columbia University

8. Bhat, Nikhil. Tractable approximation algorithms for high dimensional sequential optimization problems.

Degree: 2016, Columbia University

 Sequential decision making problems are ubiquitous in a number of research areas such as operations research, finance, engineering and computer science. The main challenge with… (more)

Subjects/Keywords: Dynamic programming; Stochastic approximation; Stochastic control theory; Markov processes; Operations research

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APA (6th Edition):

Bhat, N. (2016). Tractable approximation algorithms for high dimensional sequential optimization problems. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8JQ10W8

Chicago Manual of Style (16th Edition):

Bhat, Nikhil. “Tractable approximation algorithms for high dimensional sequential optimization problems.” 2016. Doctoral Dissertation, Columbia University. Accessed October 19, 2019. https://doi.org/10.7916/D8JQ10W8.

MLA Handbook (7th Edition):

Bhat, Nikhil. “Tractable approximation algorithms for high dimensional sequential optimization problems.” 2016. Web. 19 Oct 2019.

Vancouver:

Bhat N. Tractable approximation algorithms for high dimensional sequential optimization problems. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2019 Oct 19]. Available from: https://doi.org/10.7916/D8JQ10W8.

Council of Science Editors:

Bhat N. Tractable approximation algorithms for high dimensional sequential optimization problems. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8JQ10W8


Indian Institute of Science

9. Reddy, Danda Sai Koti. Stochastic Newton Methods With Enhanced Hessian Estimation.

Degree: 2017, Indian Institute of Science

 Optimization problems involving uncertainties are common in a variety of engineering disciplines such as transportation systems, manufacturing, communication networks, healthcare and finance. The large number… (more)

Subjects/Keywords: Stochastic Newton Methods; Hessian Estimation; Simultaneous Perturbation Stochastic Approximation (SPSA); Random Directions Stochastic Approximation (RDSA); Finite-difference Stochastic Approximation (FDSA); Hessian Estimation Scheme; Computer Science

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APA (6th Edition):

Reddy, D. S. K. (2017). Stochastic Newton Methods With Enhanced Hessian Estimation. (Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ernet.in/2005/3582 ; http://etd.iisc.ernet.in/abstracts/4450/G28169-Abs.pdf

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

Chicago Manual of Style (16th Edition):

Reddy, Danda Sai Koti. “Stochastic Newton Methods With Enhanced Hessian Estimation.” 2017. Thesis, Indian Institute of Science. Accessed October 19, 2019. http://etd.iisc.ernet.in/2005/3582 ; http://etd.iisc.ernet.in/abstracts/4450/G28169-Abs.pdf.

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

MLA Handbook (7th Edition):

Reddy, Danda Sai Koti. “Stochastic Newton Methods With Enhanced Hessian Estimation.” 2017. Web. 19 Oct 2019.

Vancouver:

Reddy DSK. Stochastic Newton Methods With Enhanced Hessian Estimation. [Internet] [Thesis]. Indian Institute of Science; 2017. [cited 2019 Oct 19]. Available from: http://etd.iisc.ernet.in/2005/3582 ; http://etd.iisc.ernet.in/abstracts/4450/G28169-Abs.pdf.

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

Council of Science Editors:

Reddy DSK. Stochastic Newton Methods With Enhanced Hessian Estimation. [Thesis]. Indian Institute of Science; 2017. Available from: http://etd.iisc.ernet.in/2005/3582 ; http://etd.iisc.ernet.in/abstracts/4450/G28169-Abs.pdf

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

10. Ait El Faqir, Marouane. Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain.

Degree: Docteur es, Automatique, 2016, Lyon

L'approche de la biologie des systèmes vise à intégrer les méthodologies appliquées dans la conception et l'analyse des systèmes technologiques complexes, au sein de la… (more)

Subjects/Keywords: Optimisation stochastique; Méthodes du Premier Ordre; Optimisation déterministe; Approximation Stochastique; RBA; Stochastic optimization; First Order Methods; Deterministic optimisation; Stochastic Approximation; RBA

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APA (6th Edition):

Ait El Faqir, M. (2016). Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain. (Doctoral Dissertation). Lyon. Retrieved from http://www.theses.fr/2016LYSEC036

Chicago Manual of Style (16th Edition):

Ait El Faqir, Marouane. “Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain.” 2016. Doctoral Dissertation, Lyon. Accessed October 19, 2019. http://www.theses.fr/2016LYSEC036.

MLA Handbook (7th Edition):

Ait El Faqir, Marouane. “Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain.” 2016. Web. 19 Oct 2019.

Vancouver:

Ait El Faqir M. Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain. [Internet] [Doctoral dissertation]. Lyon; 2016. [cited 2019 Oct 19]. Available from: http://www.theses.fr/2016LYSEC036.

Council of Science Editors:

Ait El Faqir M. Prédiction de la structure de contrôle de bactéries par optimisation sous incertitude : Magnetic resonance elastography : contributions to acquisition and reconstruction of the shear modulus : association with quasi-static ultrasound elastography to study the effect of pre-strain. [Doctoral Dissertation]. Lyon; 2016. Available from: http://www.theses.fr/2016LYSEC036


Loughborough University

11. Yevik, Andrei. Numerical approximations to the stationary solutions of stochastic differential equations.

Degree: 2011, Loughborough University

 This thesis investigates the possibility of approximating stationary solutions of stochastic differential equations using numerical methods. We consider a particular class of stochastic differential equations,… (more)

Subjects/Keywords: 511.4; Random dynamical system : Stochastic differential equation : Stochastic stationery solution : Numerical approximation : Euler’s method

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APA (6th Edition):

Yevik, A. (2011). Numerical approximations to the stationary solutions of stochastic differential equations. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/7777 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551266

Chicago Manual of Style (16th Edition):

Yevik, Andrei. “Numerical approximations to the stationary solutions of stochastic differential equations.” 2011. Doctoral Dissertation, Loughborough University. Accessed October 19, 2019. https://dspace.lboro.ac.uk/2134/7777 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551266.

MLA Handbook (7th Edition):

Yevik, Andrei. “Numerical approximations to the stationary solutions of stochastic differential equations.” 2011. Web. 19 Oct 2019.

Vancouver:

Yevik A. Numerical approximations to the stationary solutions of stochastic differential equations. [Internet] [Doctoral dissertation]. Loughborough University; 2011. [cited 2019 Oct 19]. Available from: https://dspace.lboro.ac.uk/2134/7777 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551266.

Council of Science Editors:

Yevik A. Numerical approximations to the stationary solutions of stochastic differential equations. [Doctoral Dissertation]. Loughborough University; 2011. Available from: https://dspace.lboro.ac.uk/2134/7777 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551266


Loughborough University

12. Yevik, Andrei. Numerical approximations to the stationary solutions of stochastic differential equations.

Degree: PhD, 2011, Loughborough University

 This thesis investigates the possibility of approximating stationary solutions of stochastic differential equations using numerical methods. We consider a particular class of stochastic differential equations,… (more)

Subjects/Keywords: 511.4; Random dynamical system; Stochastic differential equation; Stochastic stationery solution; Numerical approximation; Euler’s method

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APA (6th Edition):

Yevik, A. (2011). Numerical approximations to the stationary solutions of stochastic differential equations. (Doctoral Dissertation). Loughborough University. Retrieved from http://hdl.handle.net/2134/7777

Chicago Manual of Style (16th Edition):

Yevik, Andrei. “Numerical approximations to the stationary solutions of stochastic differential equations.” 2011. Doctoral Dissertation, Loughborough University. Accessed October 19, 2019. http://hdl.handle.net/2134/7777.

MLA Handbook (7th Edition):

Yevik, Andrei. “Numerical approximations to the stationary solutions of stochastic differential equations.” 2011. Web. 19 Oct 2019.

Vancouver:

Yevik A. Numerical approximations to the stationary solutions of stochastic differential equations. [Internet] [Doctoral dissertation]. Loughborough University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/2134/7777.

Council of Science Editors:

Yevik A. Numerical approximations to the stationary solutions of stochastic differential equations. [Doctoral Dissertation]. Loughborough University; 2011. Available from: http://hdl.handle.net/2134/7777

13. Saha, Roshmik. On Consistent Mapping in Distributed Environments using Mobile Sensors.

Degree: 2011, Texas A&M University

 The problem of robotic mapping, also known as simultaneous localization and mapping (SLAM), by a mobile agent for large distributed environments is addressed in this… (more)

Subjects/Keywords: SLAM; Mapping; Stochastic Approximation

…frequentist mapping technique based on stochastic approximation is introduced which provides an… …very mild assumptions using stochastic approximation techniques. • In appendix B, the… …distributed environment is estimated using a novel stochastic approximation based algorithm which we… …a solid foundation in stochastic 20 approximation literature and is provably consistent… …achieve SPLAM. This dissertation introduces “Frequentist mapping”, a novel stochastic… 

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APA (6th Edition):

Saha, R. (2011). On Consistent Mapping in Distributed Environments using Mobile Sensors. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9718

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):

Saha, Roshmik. “On Consistent Mapping in Distributed Environments using Mobile Sensors.” 2011. Thesis, Texas A&M University. Accessed October 19, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9718.

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

MLA Handbook (7th Edition):

Saha, Roshmik. “On Consistent Mapping in Distributed Environments using Mobile Sensors.” 2011. Web. 19 Oct 2019.

Vancouver:

Saha R. On Consistent Mapping in Distributed Environments using Mobile Sensors. [Internet] [Thesis]. Texas A&M University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9718.

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

Council of Science Editors:

Saha R. On Consistent Mapping in Distributed Environments using Mobile Sensors. [Thesis]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9718

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


Texas A&M University

14. Lin, Fang-Yu. Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data.

Degree: 2014, Texas A&M University

 Modeling and mining with massive volumes of data have become popular in recent decades. However, it is difficult to analyze on a single commodity computer… (more)

Subjects/Keywords: Stochastic Approximation Monte Carlo; Parallel Computation; MCMC; Big Data

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APA (6th Edition):

Lin, F. (2014). Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153814

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):

Lin, Fang-Yu. “Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data.” 2014. Thesis, Texas A&M University. Accessed October 19, 2019. http://hdl.handle.net/1969.1/153814.

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

MLA Handbook (7th Edition):

Lin, Fang-Yu. “Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data.” 2014. Web. 19 Oct 2019.

Vancouver:

Lin F. Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1969.1/153814.

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

Council of Science Editors:

Lin F. Combining Strategies for Parallel Stochastic Approximation Monte Carlo Algorithm of Big Data. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153814

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


Cornell University

15. Spencer, Gwen. Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability .

Degree: 2012, Cornell University

 As ecologists and foresters produce an increasing range of probabilistic data, mathematical techniques that address the fundamental interactions between stochastic events and spatial landscape features… (more)

Subjects/Keywords: Optimization; Algorithms; Approximation; Stochastic; Graph Theory; Sustainability; Natural Resources

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APA (6th Edition):

Spencer, G. (2012). Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/31423

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):

Spencer, Gwen. “Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability .” 2012. Thesis, Cornell University. Accessed October 19, 2019. http://hdl.handle.net/1813/31423.

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

MLA Handbook (7th Edition):

Spencer, Gwen. “Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability .” 2012. Web. 19 Oct 2019.

Vancouver:

Spencer G. Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability . [Internet] [Thesis]. Cornell University; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1813/31423.

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

Council of Science Editors:

Spencer G. Approximation Algorithms For Stochastic Combinatorial Optimization, With Applications In Sustainability . [Thesis]. Cornell University; 2012. Available from: http://hdl.handle.net/1813/31423

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


Carnegie Mellon University

16. Krishnaswamy, Ravishankar. Approximation Techniques for Stochastic Combinatorial Optimization Problems.

Degree: 2012, Carnegie Mellon University

 The focus of this thesis is on the design and analysis of algorithms for basic problems in Stochastic Optimization, specifically a class of fundamental combinatorial… (more)

Subjects/Keywords: Approximation Algorithms; Stochastic Optimization; Network Design; Scheduling; Computer Sciences

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APA (6th Edition):

Krishnaswamy, R. (2012). Approximation Techniques for Stochastic Combinatorial Optimization Problems. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/157

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):

Krishnaswamy, Ravishankar. “Approximation Techniques for Stochastic Combinatorial Optimization Problems.” 2012. Thesis, Carnegie Mellon University. Accessed October 19, 2019. http://repository.cmu.edu/dissertations/157.

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

MLA Handbook (7th Edition):

Krishnaswamy, Ravishankar. “Approximation Techniques for Stochastic Combinatorial Optimization Problems.” 2012. Web. 19 Oct 2019.

Vancouver:

Krishnaswamy R. Approximation Techniques for Stochastic Combinatorial Optimization Problems. [Internet] [Thesis]. Carnegie Mellon University; 2012. [cited 2019 Oct 19]. Available from: http://repository.cmu.edu/dissertations/157.

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

Council of Science Editors:

Krishnaswamy R. Approximation Techniques for Stochastic Combinatorial Optimization Problems. [Thesis]. Carnegie Mellon University; 2012. Available from: http://repository.cmu.edu/dissertations/157

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


Louisiana State University

17. Duan, Qinglin. A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty.

Degree: PhD, Engineering Science and Materials, 2013, Louisiana State University

 The need for inventory control models for practical real-world applications is growing with the global expansion of supply chains. The widely used traditional optimization procedures… (more)

Subjects/Keywords: Healthcare Blood Products; Crossmatching; Perishable; Stochastic; Sample Average Approximation

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

APA (6th Edition):

Duan, Q. (2013). A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-10222013-115111 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1219

Chicago Manual of Style (16th Edition):

Duan, Qinglin. “A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty.” 2013. Doctoral Dissertation, Louisiana State University. Accessed October 19, 2019. etd-10222013-115111 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1219.

MLA Handbook (7th Edition):

Duan, Qinglin. “A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty.” 2013. Web. 19 Oct 2019.

Vancouver:

Duan Q. A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2019 Oct 19]. Available from: etd-10222013-115111 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1219.

Council of Science Editors:

Duan Q. A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-10222013-115111 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1219

18. Jum, Ernest. Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps.

Degree: 2015, University of Tennessee – Knoxville

 In this dissertation, we consider the problem of simulation of stochastic differential equations driven by pure jump Levy processes with infinite jump activity. Examples include,… (more)

Subjects/Keywords: stochastic differential equation; numerical approximation; Levy motion; infinitely many jumps; Probability

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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

APA (6th Edition):

Jum, E. (2015). Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/3430

Chicago Manual of Style (16th Edition):

Jum, Ernest. “Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps.” 2015. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed October 19, 2019. https://trace.tennessee.edu/utk_graddiss/3430.

MLA Handbook (7th Edition):

Jum, Ernest. “Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps.” 2015. Web. 19 Oct 2019.

Vancouver:

Jum E. Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2015. [cited 2019 Oct 19]. Available from: https://trace.tennessee.edu/utk_graddiss/3430.

Council of Science Editors:

Jum E. Numerical Approximation of Stochastic Differential Equations Driven by Levy Motion with Infinitely Many Jumps. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2015. Available from: https://trace.tennessee.edu/utk_graddiss/3430


University of Florida

19. Zhou, Zhiqiang. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.

Degree: MS, Industrial and Systems Engineering, 2014, University of Florida

 The main goal of this paper is to develop a new stochastic subgradient method for constrained stochastic convex optimization problems. The problem we are interested… (more)

Subjects/Keywords: Approximation; Entropy; Estimated cost to complete; Keywords; optimization  – rubust  – stochastic

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

APA (6th Edition):

Zhou, Z. (2014). Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047301

Chicago Manual of Style (16th Edition):

Zhou, Zhiqiang. “Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.” 2014. Masters Thesis, University of Florida. Accessed October 19, 2019. http://ufdc.ufl.edu/UFE0047301.

MLA Handbook (7th Edition):

Zhou, Zhiqiang. “Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.” 2014. Web. 19 Oct 2019.

Vancouver:

Zhou Z. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. [Internet] [Masters thesis]. University of Florida; 2014. [cited 2019 Oct 19]. Available from: http://ufdc.ufl.edu/UFE0047301.

Council of Science Editors:

Zhou Z. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. [Masters Thesis]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047301


McMaster University

20. Griscik, Michael Paul. A New Algorithm for Stochastic Approximation.

Degree: MEngr, 1970, McMaster University

A review of Stochastic Approximation and the major contributions to the area is made. A proof of convergence for the algorithm is developed. An… (more)

Subjects/Keywords: stochastic; algorithm; approximation; convergence; optimization

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APA (6th Edition):

Griscik, M. P. (1970). A New Algorithm for Stochastic Approximation. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/17894

Chicago Manual of Style (16th Edition):

Griscik, Michael Paul. “A New Algorithm for Stochastic Approximation.” 1970. Masters Thesis, McMaster University. Accessed October 19, 2019. http://hdl.handle.net/11375/17894.

MLA Handbook (7th Edition):

Griscik, Michael Paul. “A New Algorithm for Stochastic Approximation.” 1970. Web. 19 Oct 2019.

Vancouver:

Griscik MP. A New Algorithm for Stochastic Approximation. [Internet] [Masters thesis]. McMaster University; 1970. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/11375/17894.

Council of Science Editors:

Griscik MP. A New Algorithm for Stochastic Approximation. [Masters Thesis]. McMaster University; 1970. Available from: http://hdl.handle.net/11375/17894


University of Waterloo

21. Linhares Rodrigues, Andre. Approximation Algorithms for Distributionally Robust Stochastic Optimization.

Degree: 2019, University of Waterloo

 Two-stage stochastic optimization is a widely used framework for modeling uncertainty, where we have a probability distribution over possible realizations of the data, called scenarios,… (more)

Subjects/Keywords: approximation algorithms; stochastic optimization; discrete optimization; convex optimization

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APA (6th Edition):

Linhares Rodrigues, A. (2019). Approximation Algorithms for Distributionally Robust Stochastic Optimization. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14639

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):

Linhares Rodrigues, Andre. “Approximation Algorithms for Distributionally Robust Stochastic Optimization.” 2019. Thesis, University of Waterloo. Accessed October 19, 2019. http://hdl.handle.net/10012/14639.

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

MLA Handbook (7th Edition):

Linhares Rodrigues, Andre. “Approximation Algorithms for Distributionally Robust Stochastic Optimization.” 2019. Web. 19 Oct 2019.

Vancouver:

Linhares Rodrigues A. Approximation Algorithms for Distributionally Robust Stochastic Optimization. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10012/14639.

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

Council of Science Editors:

Linhares Rodrigues A. Approximation Algorithms for Distributionally Robust Stochastic Optimization. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14639

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


North Carolina State University

22. Ruan, Chen. Recursive Quantile Estimation with Application to Value at Risk.

Degree: PhD, Statistics, 2008, North Carolina State University

Subjects/Keywords: regression quantile; stochastic approximation

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APA (6th Edition):

Ruan, C. (2008). Recursive Quantile Estimation with Application to Value at Risk. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4259

Chicago Manual of Style (16th Edition):

Ruan, Chen. “Recursive Quantile Estimation with Application to Value at Risk.” 2008. Doctoral Dissertation, North Carolina State University. Accessed October 19, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4259.

MLA Handbook (7th Edition):

Ruan, Chen. “Recursive Quantile Estimation with Application to Value at Risk.” 2008. Web. 19 Oct 2019.

Vancouver:

Ruan C. Recursive Quantile Estimation with Application to Value at Risk. [Internet] [Doctoral dissertation]. North Carolina State University; 2008. [cited 2019 Oct 19]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4259.

Council of Science Editors:

Ruan C. Recursive Quantile Estimation with Application to Value at Risk. [Doctoral Dissertation]. North Carolina State University; 2008. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4259


Queens University

23. Saldi, Naci. Optimal Quantization and Approximation in Source Coding and Stochastic Control .

Degree: Mathematics and Statistics, 2015, Queens University

 This thesis deals with non-standard optimal quantization and approximation problems in source coding and stochastic control. The first part of the thesis considers randomized quantization.… (more)

Subjects/Keywords: Quantization; randomized quantization; Markov decision processes; approximation in stochastic control

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APA (6th Edition):

Saldi, N. (2015). Optimal Quantization and Approximation in Source Coding and Stochastic Control . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/13147

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):

Saldi, Naci. “Optimal Quantization and Approximation in Source Coding and Stochastic Control .” 2015. Thesis, Queens University. Accessed October 19, 2019. http://hdl.handle.net/1974/13147.

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

MLA Handbook (7th Edition):

Saldi, Naci. “Optimal Quantization and Approximation in Source Coding and Stochastic Control .” 2015. Web. 19 Oct 2019.

Vancouver:

Saldi N. Optimal Quantization and Approximation in Source Coding and Stochastic Control . [Internet] [Thesis]. Queens University; 2015. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1974/13147.

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

Council of Science Editors:

Saldi N. Optimal Quantization and Approximation in Source Coding and Stochastic Control . [Thesis]. Queens University; 2015. Available from: http://hdl.handle.net/1974/13147

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


Michigan State University

24. Obremski, Thomas Edward, 1944-. A Kiefer-Wolfowitz type stochastic approximation procedure.

Degree: PhD, Department of Statistics and Probability, 1976, Michigan State University

Subjects/Keywords: Approximation theory; Stochastic analysis

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APA (6th Edition):

Obremski, Thomas Edward, 1. (1976). A Kiefer-Wolfowitz type stochastic approximation procedure. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:46667

Chicago Manual of Style (16th Edition):

Obremski, Thomas Edward, 1944-. “A Kiefer-Wolfowitz type stochastic approximation procedure.” 1976. Doctoral Dissertation, Michigan State University. Accessed October 19, 2019. http://etd.lib.msu.edu/islandora/object/etd:46667.

MLA Handbook (7th Edition):

Obremski, Thomas Edward, 1944-. “A Kiefer-Wolfowitz type stochastic approximation procedure.” 1976. Web. 19 Oct 2019.

Vancouver:

Obremski, Thomas Edward 1. A Kiefer-Wolfowitz type stochastic approximation procedure. [Internet] [Doctoral dissertation]. Michigan State University; 1976. [cited 2019 Oct 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:46667.

Council of Science Editors:

Obremski, Thomas Edward 1. A Kiefer-Wolfowitz type stochastic approximation procedure. [Doctoral Dissertation]. Michigan State University; 1976. Available from: http://etd.lib.msu.edu/islandora/object/etd:46667


Michigan State University

25. Abdelhamid, Sami Naguib, 1938-. Transformation of observations in Stochastis approximation.

Degree: PhD, Department of Statistics and Probability, 1971, Michigan State University

Subjects/Keywords: Stochastic processes; Approximation theory

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APA (6th Edition):

Abdelhamid, Sami Naguib, 1. (1971). Transformation of observations in Stochastis approximation. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:46668

Chicago Manual of Style (16th Edition):

Abdelhamid, Sami Naguib, 1938-. “Transformation of observations in Stochastis approximation.” 1971. Doctoral Dissertation, Michigan State University. Accessed October 19, 2019. http://etd.lib.msu.edu/islandora/object/etd:46668.

MLA Handbook (7th Edition):

Abdelhamid, Sami Naguib, 1938-. “Transformation of observations in Stochastis approximation.” 1971. Web. 19 Oct 2019.

Vancouver:

Abdelhamid, Sami Naguib 1. Transformation of observations in Stochastis approximation. [Internet] [Doctoral dissertation]. Michigan State University; 1971. [cited 2019 Oct 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:46668.

Council of Science Editors:

Abdelhamid, Sami Naguib 1. Transformation of observations in Stochastis approximation. [Doctoral Dissertation]. Michigan State University; 1971. Available from: http://etd.lib.msu.edu/islandora/object/etd:46668


Northeastern University

26. Huang, Kuo-Lun. Efficient algorithms for stochastic decoding of LDPC codes.

Degree: PhD, Department of Electrical and Computer Engineering, 2016, Northeastern University

 The expanding demand for high-speed communications has resulted in development of high-throughput error-correcting techniques required by emerging communication standards. Low-Density Parity-Check (LDPC) codes are a… (more)

Subjects/Keywords: low-density parity-check; stochastic computation; decoding; Decoders (Electronics); Error-correcting codes (Information theory); Coding theory; Stochastic processes; Stochastic approximation; Algorithms

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APA (6th Edition):

Huang, K. (2016). Efficient algorithms for stochastic decoding of LDPC codes. (Doctoral Dissertation). Northeastern University. Retrieved from http://hdl.handle.net/2047/D20211572

Chicago Manual of Style (16th Edition):

Huang, Kuo-Lun. “Efficient algorithms for stochastic decoding of LDPC codes.” 2016. Doctoral Dissertation, Northeastern University. Accessed October 19, 2019. http://hdl.handle.net/2047/D20211572.

MLA Handbook (7th Edition):

Huang, Kuo-Lun. “Efficient algorithms for stochastic decoding of LDPC codes.” 2016. Web. 19 Oct 2019.

Vancouver:

Huang K. Efficient algorithms for stochastic decoding of LDPC codes. [Internet] [Doctoral dissertation]. Northeastern University; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/2047/D20211572.

Council of Science Editors:

Huang K. Efficient algorithms for stochastic decoding of LDPC codes. [Doctoral Dissertation]. Northeastern University; 2016. Available from: http://hdl.handle.net/2047/D20211572


University of Florida

27. Jiang, Ruiwei. Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness.

Degree: PhD, Industrial and Systems Engineering, 2013, University of Florida

 Decision making processes in practice often involve trade-offs between reliability and cost effectiveness. When a decision maker is faced with an uncertain environment, more often… (more)

Subjects/Keywords: Algorithms; Ambiguity; Approximation; Cost functions; Infinity; Linear programming; Probability distributions; Renewable energy; Sample size; Stochastic models; cost  – optimization  – reliability  – stochastic

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APA (6th Edition):

Jiang, R. (2013). Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045885

Chicago Manual of Style (16th Edition):

Jiang, Ruiwei. “Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness.” 2013. Doctoral Dissertation, University of Florida. Accessed October 19, 2019. http://ufdc.ufl.edu/UFE0045885.

MLA Handbook (7th Edition):

Jiang, Ruiwei. “Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness.” 2013. Web. 19 Oct 2019.

Vancouver:

Jiang R. Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 19]. Available from: http://ufdc.ufl.edu/UFE0045885.

Council of Science Editors:

Jiang R. Data-Driven Stochastic Optimization Integrating Reliability with Cost Effectiveness. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045885


Mississippi State University

28. Emelogu, Adindu Ahurueze. Optimal supply chain configuration for the additive manufacturing of biomedical implants.

Degree: PhD, Industrial and Systems Engineering, 2016, Mississippi State University

  In this dissertation, we study two important problems related to additive manufacturing (AM). In the first part, we investigate the economic feasibility of using… (more)

Subjects/Keywords: clustering; enhanced sample average approximation; sample average approximation; deployment configuration; large scale supply chain; continuous approximation; Additive manufacturing; biomedical implants; stochastic programming model

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APA (6th Edition):

Emelogu, A. A. (2016). Optimal supply chain configuration for the additive manufacturing of biomedical implants. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-10192016-124949/ ;

Chicago Manual of Style (16th Edition):

Emelogu, Adindu Ahurueze. “Optimal supply chain configuration for the additive manufacturing of biomedical implants.” 2016. Doctoral Dissertation, Mississippi State University. Accessed October 19, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-10192016-124949/ ;.

MLA Handbook (7th Edition):

Emelogu, Adindu Ahurueze. “Optimal supply chain configuration for the additive manufacturing of biomedical implants.” 2016. Web. 19 Oct 2019.

Vancouver:

Emelogu AA. Optimal supply chain configuration for the additive manufacturing of biomedical implants. [Internet] [Doctoral dissertation]. Mississippi State University; 2016. [cited 2019 Oct 19]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-10192016-124949/ ;.

Council of Science Editors:

Emelogu AA. Optimal supply chain configuration for the additive manufacturing of biomedical implants. [Doctoral Dissertation]. Mississippi State University; 2016. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-10192016-124949/ ;


University of Alberta

29. Maei, Hamid Reza. Gradient Temporal-Difference Learning Algorithms.

Degree: PhD, Department of Computing Science, 2011, University of Alberta

 We present a new family of gradient temporal-difference (TD) learning methods with function approximation whose complexity, both in terms of memory and per-time-step computation, scales… (more)

Subjects/Keywords: Policy Evaluation; Temporal-Difference learning; Reinforcement Learning; Stochastic Gradient-Descent; Value Function Approximation

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APA (6th Edition):

Maei, H. R. (2011). Gradient Temporal-Difference Learning Algorithms. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/8s45q967t

Chicago Manual of Style (16th Edition):

Maei, Hamid Reza. “Gradient Temporal-Difference Learning Algorithms.” 2011. Doctoral Dissertation, University of Alberta. Accessed October 19, 2019. https://era.library.ualberta.ca/files/8s45q967t.

MLA Handbook (7th Edition):

Maei, Hamid Reza. “Gradient Temporal-Difference Learning Algorithms.” 2011. Web. 19 Oct 2019.

Vancouver:

Maei HR. Gradient Temporal-Difference Learning Algorithms. [Internet] [Doctoral dissertation]. University of Alberta; 2011. [cited 2019 Oct 19]. Available from: https://era.library.ualberta.ca/files/8s45q967t.

Council of Science Editors:

Maei HR. Gradient Temporal-Difference Learning Algorithms. [Doctoral Dissertation]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/8s45q967t


Texas A&M University

30. De, Debkumar. Essays on Bayesian Time Series and Variable Selection.

Degree: 2014, Texas A&M University

 Estimating model parameters in dynamic model continues to be challenge. In my dissertation, we have introduced a Stochastic Approximation based parameter estimation approach under Ensemble… (more)

Subjects/Keywords: Ensemble Kalman Filter; Stochastic Approximation; Non-parametric Regression; Matrix variate regression; Variable selection

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APA (6th Edition):

De, D. (2014). Essays on Bayesian Time Series and Variable Selection. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152793

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):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Thesis, Texas A&M University. Accessed October 19, 2019. http://hdl.handle.net/1969.1/152793.

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

MLA Handbook (7th Edition):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Web. 19 Oct 2019.

Vancouver:

De D. Essays on Bayesian Time Series and Variable Selection. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1969.1/152793.

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

Council of Science Editors:

De D. Essays on Bayesian Time Series and Variable Selection. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152793

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

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