CPSC-658 Randomized Algorithms

Lecture Notes

• Lecture Notes #1, Karger's min-cut algorithm
• Lecture Notes #2, Karger-Stein's min-cut algorithm
• Lecture Notes #3, Basic probability theory
• Lecture Notes #4, Does randomness help solving NP-hard problems?
• Lecture Notes #5, How to count: sampling and allocation
• Lecture Notes #6, The path problem and color-coding
• Lecture Notes #7, Randomized divide-and-conquer based on solutions
• Lecture Notes #8, Random variables and expectation
• Lecture Notes #9, Analysis of algorithm expected complexity
• Lecture Notes #10, Variance and Chebyshev's Inequality
• References

Supplementary Reading

• J. Chen and S. Lu
  "Improved parameterized set splitting algorithms: a probabilistic approach,"
  Algorithmica 54, pp. 472-489, 2009.
• J. Chen, J. Kneis, S. Lu, D. Molle, S. Richter, P. Rossmanith, S.-H. Sze, and F. Zhang
  "Randomized divide-and-conquer: improved path, matching, and packing algorithms,"
  SIAM Journal on Computing 38-6, pp. 2526-2547, 2009.