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You searched for +publisher:"Clemson University" +contributor:("Dr. Matthew Saltzman"). Showing records 1 – 5 of 5 total matches.

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1. Wei, Tianhui. Variable Selection for Complex Data with Sparsity: An Application in GWAS.

Degree: PhD, Mathematical Sciences, 2018, Clemson University

 In this dissertation, we investigate the limitations of several methods that have been proposed for variable selection in recent decades, and in particular we explore… (more)

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APA (6th Edition):

Wei, T. (2018). Variable Selection for Complex Data with Sparsity: An Application in GWAS. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2178

Chicago Manual of Style (16th Edition):

Wei, Tianhui. “Variable Selection for Complex Data with Sparsity: An Application in GWAS.” 2018. Doctoral Dissertation, Clemson University. Accessed September 26, 2020. https://tigerprints.clemson.edu/all_dissertations/2178.

MLA Handbook (7th Edition):

Wei, Tianhui. “Variable Selection for Complex Data with Sparsity: An Application in GWAS.” 2018. Web. 26 Sep 2020.

Vancouver:

Wei T. Variable Selection for Complex Data with Sparsity: An Application in GWAS. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2020 Sep 26]. Available from: https://tigerprints.clemson.edu/all_dissertations/2178.

Council of Science Editors:

Wei T. Variable Selection for Complex Data with Sparsity: An Application in GWAS. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2178

2. McIntyre, Lauren Paige. Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator.

Degree: MS, Mathematical Sciences, 2017, Clemson University

 In this thesis, we present a 1D model for the complex phenomenon of cross-flow filtration. We begin by developing the governing equations and providing analytical… (more)

Subjects/Keywords: cross flow filtration; modeling filtration; web application; web calculator

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APA (6th Edition):

McIntyre, L. P. (2017). Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator. (Masters Thesis). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_theses/2783

Chicago Manual of Style (16th Edition):

McIntyre, Lauren Paige. “Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator.” 2017. Masters Thesis, Clemson University. Accessed September 26, 2020. https://tigerprints.clemson.edu/all_theses/2783.

MLA Handbook (7th Edition):

McIntyre, Lauren Paige. “Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator.” 2017. Web. 26 Sep 2020.

Vancouver:

McIntyre LP. Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator. [Internet] [Masters thesis]. Clemson University; 2017. [cited 2020 Sep 26]. Available from: https://tigerprints.clemson.edu/all_theses/2783.

Council of Science Editors:

McIntyre LP. Cross Flow Filtration Modeling Using Analytical and Numerical Solutions Along with Implementation as a Web-Based Calculator. [Masters Thesis]. Clemson University; 2017. Available from: https://tigerprints.clemson.edu/all_theses/2783

3. Xu, Yibo. Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions.

Degree: PhD, Mathematical Sciences, 2018, Clemson University

  Motivated by a variety of problems in global optimization and integer programming that involve multilinear expressions of discrete or continuous variables, this research derives… (more)

Subjects/Keywords: convex hull; error analysis; facet; multilinear polynomial; symmetry

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APA (6th Edition):

Xu, Y. (2018). Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2094

Chicago Manual of Style (16th Edition):

Xu, Yibo. “Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions.” 2018. Doctoral Dissertation, Clemson University. Accessed September 26, 2020. https://tigerprints.clemson.edu/all_dissertations/2094.

MLA Handbook (7th Edition):

Xu, Yibo. “Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions.” 2018. Web. 26 Sep 2020.

Vancouver:

Xu Y. Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2020 Sep 26]. Available from: https://tigerprints.clemson.edu/all_dissertations/2094.

Council of Science Editors:

Xu Y. Convex Hulls, Relaxations, and Approximations of General Monomials and Multilinear Functions. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2094

4. Dranichak, Garrett M. Robust Solutions to Uncertain Multiobjective Programs.

Degree: PhD, Mathematical Sciences, 2018, Clemson University

 Decision making in the presence of uncertainty and multiple conflicting objec-tives is a real-life issue, especially in the fields of engineering, public policy making, business… (more)

Subjects/Keywords: highly robust efficient; objective-wise uncertainty; robust multiobjective optimization; uncertain multiobjective programs

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APA (6th Edition):

Dranichak, G. M. (2018). Robust Solutions to Uncertain Multiobjective Programs. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2154

Chicago Manual of Style (16th Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Doctoral Dissertation, Clemson University. Accessed September 26, 2020. https://tigerprints.clemson.edu/all_dissertations/2154.

MLA Handbook (7th Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Web. 26 Sep 2020.

Vancouver:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2020 Sep 26]. Available from: https://tigerprints.clemson.edu/all_dissertations/2154.

Council of Science Editors:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2154

5. Adelgren, Nathan. Solution Techniques for Classes of Biobjective and Parametric Programs.

Degree: PhD, Mathematical Science, 2016, Clemson University

 Mathematical optimization, or mathematical programming, has been studied for several decades. Researchers are constantly searching for optimization techniques which allow one to de-termine the ideal… (more)

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APA (6th Edition):

Adelgren, N. (2016). Solution Techniques for Classes of Biobjective and Parametric Programs. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1754

Chicago Manual of Style (16th Edition):

Adelgren, Nathan. “Solution Techniques for Classes of Biobjective and Parametric Programs.” 2016. Doctoral Dissertation, Clemson University. Accessed September 26, 2020. https://tigerprints.clemson.edu/all_dissertations/1754.

MLA Handbook (7th Edition):

Adelgren, Nathan. “Solution Techniques for Classes of Biobjective and Parametric Programs.” 2016. Web. 26 Sep 2020.

Vancouver:

Adelgren N. Solution Techniques for Classes of Biobjective and Parametric Programs. [Internet] [Doctoral dissertation]. Clemson University; 2016. [cited 2020 Sep 26]. Available from: https://tigerprints.clemson.edu/all_dissertations/1754.

Council of Science Editors:

Adelgren N. Solution Techniques for Classes of Biobjective and Parametric Programs. [Doctoral Dissertation]. Clemson University; 2016. Available from: https://tigerprints.clemson.edu/all_dissertations/1754

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