Department of Computer Science and Technology

Course pages 2018–19

Probability and Computation

*** Mock Exam *** (solutions)

Lecture notes

  • Lecture 1: Introduction (slides)
  • Lecture 2: Markov Chains (slides)
  • Lecture 3: Coupling and Convergence (slides)
  • Lecture 4: Card Shuffling and Covertime (slides, print)
  • Lecture 5: Concentration Inequalities (slides)
  • Lecture 6: Concentration Inequalities - Introduction to Martingales (slides)
  • Lecture 7: Martingales and Concentration (slides)
  • Lecture 8: The Optional Stopping Theorem (slides)
  • Lecture 9: Linear algebra review and Markov chains (slides)
  • Lecture 10: Mixing time and eigenvalues (slides)
  • Lecture 11: Graph clustering and random walks (slides, example)
  • Lecture 12: Graph clustering and beyond (slides)
  • Lecture 13-14: Sublinear-Time Algorithms (slides, print)
  • Lecture 15: Dimensionality Reduction (slides)

Problem sheets


Solutions to exercises


Additional material