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Course Criteria
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3.00 Credits
Credits: 3 Cross-Listed with OR 780 Studies analytical modeling of computer and communication networks and performance evaluations. Topics include Markovian systems, open networks, closed networks, approximations, decomposition, simulation, sensitivity analysis, and optimal operation of systems. Presents local area networks, manufacturing systems, and other applications. Prerequisites OR 645 or 647, or ECE 542; or equivalent.
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3.00 Credits
Credits: 3 Cross-Listed with OR 782 Studies problems using most recent developments. Topics include cutting plane procedures based on polyhedral combinatorics; column-generation procedures for large, complex problems; heuristic approaches such as genetic algorithms, simulated annealing, and Tabu search; study of special structures; reformulation techniques; and bounding approaches. Topics stress most recent developments in field. May be repeated for credit when topics are distinctly different. Prerequisites OR 641 and 642.
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3.00 Credits
Credits: 3 Cross-Listed with OR 783 Recent developments in solving optimization problems on networks. Prepares doctoral students to perform advanced research on network-related problems. Topics include linear, discrete, nonlinear, and stochastic problems. Several aspects of problems also studied, including computational complexity, exact algorithms, heuristics, solvable special cases, and computer implementation issues. Prerequisites OR 643.
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3.00 Credits
Credits: 3 Cross-Listed with OR 784 Studies theory and algorithms for solving nonlinear optimization problems. Contents vary; possible topics include large-scale and parallel-unconstrained optimization, theoretical issues in constrained optimization, duality theory, Lagrangian and sequential quadratic programming methods. May be repeated for credit when topics are distinctly different. Prerequisites OR 644.
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1.00 - 3.00 Credits
Credits: 1-3 Reading and research on specific topic in information technology under direction of faculty member. Notes May be repeated as needed. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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1.00 - 3.00 Credits
Credits: 1-3 Reading and research on specific topic in information technology under direction of faculty member. Notes May be repeated as needed. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 803 Individualized intensive study of particular aspects of information technology. Notes May be repeated as needed. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 804 Individualized intensive study of particular aspects of information technology. Notes May be repeated as needed. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 809 From quantitative point of view, discusses characteristics of most important technologies used to support implementation of e-business sites. Includes topics such as hardware and software architectures of e-business sites, authentication, and payment services, understanding customer behavior, workload characterization, scalability analysis, and performance prediction. Prerequisites At least one operating systems and one networking course, and admission to VSITE doctoral program. Notes Term paper and project required. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 811 Presentation of unifying principles that underlie diverse methods, paradigms, and approaches to machine earning and inference. Reviews most known learning and inference systems, discusses strengths and limitations, and suggests most appropriate areas of application. Students get hands-on experience by experimenting with state-of-the-art learning and inference systems, and working on projects tailored to research interests. Prerequisites CS 680 and 681, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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