Student presentations, which form the basis for class discussions, are available below. Full citations for the related readings can be found on the readings page.

SES # | TOPICS |
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1 | MAXCUT; Semidefinite Programming; and the Goemans-Williamson Paper, "Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming."Presentation courtesy of Rob Freund (PDF). This is a summary presentation based on: Goemans, Michel X., and David P. Williamson. "Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming." Journal of the ACM 42, no. 6 (November 1995): 1115-45. |

2 | Dunagan and Vempala Paper, "Simple Polynomial-Time Rescaling Algorithm for Solving Linear Programs."Dunagan, John, and Santosh Vempala. "A Simple Polynomial-Time Rescaling Algorithm for Solving Linear Programs." In Proceedings of the 36th Annual Association for Computing Machinery Symposium on Theory of Computing. New York, NY: ACM Press, 2004. Storn and Price Paper, "Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces." Presentation courtesy of David Craft. Used with permission (PDF). This is a summary presentation based on: Storn, Rainer, and Kenneth Price. "Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces." Journal of Global Optimization 11 (1997): 341-59. |

3 | Clarkson Paper, "Las Vegas Algorithms for Linear and Integer Programming When the Dimension Is Small."Presentation courtesy of Susan Martonosi. Used with permission (PDF). This is a summary presentation based on: Clarkson, Kenneth L. "Las Vegas Algorithms for Linear and Integer Programming When the Dimension Is Small." Journal of the ACM 42, no. 2 (March 1995): 488-99.Motwani and Raghavan, Chapter 9 in Randomized Algorithms.Presentation courtesy of Jan De Mot. Used with permission (PDF). This is a summary presentation based on: Motwani, Rajeev, and Prabhakar Raghavan. Chapter 9 in Randomized Algorithms. Cambridge, UK: Cambridge University Press, 1995. ISBN: 0-521-47465-5. |

4 | Kalai Paper #1, "A Subexponential Randomized Simplex Algorithm." Kalai Paper #2, "Linear Programming, the Simplex Algorithm and Simple Polytopes." Both presentations courtesy of Dan Stratila. Used with permission (PDF). This is a summary presentation based on two papers: Kalai, Gil. "A Subexponential Randomized Simplex Algorithm (Extended Abstract)." In Proceedings of the 24th Annual Association for Computing Machinery Symposium on Theory of Computing. New York, NY: ACM Press, 1992. and, Kalai, Gil. "Linear Programming, the Simplex Algorithm and Simple Polytopes." Jerusalem, Israel: Hebrew University of Jerusalem, May 1997. |

5 | Solis and Wets Paper, "Minimization by Random Search Techniques."Presentation courtesy of Michele Aghassi. Used with permission (PDF). This is a summary presentation based on: Solis, F. J., and R. J-B. Wets. "Minimization by Random Search Techniques." Mathematical Operations Research 6 (1981): 19-30.Romeijn Thesis Book, "Global Optimization by Random Walk Sampling Methods." |

6 | Zabinsky and Smith Paper, "Pure Adaptive Search in Global Optimization." Presentation courtesy of Michael Yee. Used with permission (PDF). This is a summary presentation based on: Zabinsky, Zelda B., and Robert L. Smith. "Pure Adaptive Search in Global Optimization." Mathematical Programming 55 (1992): 323-38.Presentation courtesy of Michael Yee and Kwong-Meng Teo. Used with permission (PDF). This is a summary presentation based on: Zabinsky, Zelda B., and Robert L. Smith. "Pure Adaptive Search in Global Optimization." Mathematical Programming 55 (1992): 323-38. |

7 | Simonovits Paper, "How to Compute the Volume in High Dimension?" |

8 | Romeijn and Smith Paper, "Simulated Annealing for Constrained Global Optimization." |

9 | Bertsimas and Vempala Paper, "Solving Convex Programs by Random Walks."Zabinsky, Smith, etc. Paper, "Improving Hit-and-Run for Global Optimization." |

10 | Zabinsky, Graesser, etc. Paper, "Global Optimization of Composite Laminates Using Improving Hit and Run."Sanjeev Paper, "Approximation Schemes for NP-hard Geometric Optimization Problems: A Survey." |