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Great Ideas in Computing Average Case Analysis

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Great Ideas in Computing. Average Case Analysis. Richard Anderson ... T(n) = ave {T(I) | I is a problem instance of size n} = sum {p(I) T(I) | I is a ... – PowerPoint PPT presentation

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Title: Great Ideas in Computing Average Case Analysis


1
Great Ideas in ComputingAverage Case Analysis
  • Richard Anderson
  • University of Washington

2
What happens on the average
3
Worst case versus average case
  • T(n) max T(I) I is a problem instance of
    size
    n
  • T(n) ave T(I) I is a problem instance of
    size n
    sum p(I) T(I) I is a problem
    instance of size n

4
Is real world data random?
  • Is real world data worst case?

5
Average case analysis
max A0 for i 1 to n-1 if A i gt
max max A i

How many times is line executed
6
Quicksort
  • Worst case runtime is n2
  • Average case is n log n

7
Random Trees
8
Euclidean TSP
9
Asymmetric TSP
  • Random Asymmetric TSP
  • n ? n matrix with random entries in 0, 1
  • Theorem
  • There is a polynomial time algorithm that gives a
    very good approximation for a random ATSP

10
Assignment Problem
  • Minimum weight perfect matching in a complete,
    bipartite graph
  • Solvable in polynomial time
  • How is the assignment problem related to the
    ATSP?

11
ATSP Algorithm
  • Solve relaxed version with Assignment Problem
  • Splice together cycles
  • Solution to the Assignment problem is a random
    permutation
  • Random permutations have a small number of cycles

12
Random Graphs
  • What is a random graph?

13
Standard model
  • Each edge is present with probability p
  • Expected degree of a vertex is pn

14
Does a random graph have a Hamiltonian circuit
15
Hamiltonian Circuit Algorithm
16
What does the Web Graph look like?
17
Degree distribution in the web graph
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