Courses

236602 Theory Lab Winter 2017/2018

This is a discovery-style class, based on work in groups during class time.

The students will work on weekly sheets:

  • Week 1 (22 Oct 2017): Fourier analysis: introduction.
  • Week 2 (29 Oct 2017): Fourier analysis: influence.
  • Week 3 (5 Nov 2017): Fourier analysis: noise.
  • Week 4 (12 Nov 2017): Fourier analysis: KKL.
  • Week 5 (19 Nov 2017): Information theory: prefix codes.
  • Week 6 (26 Nov 2017): Information theory: basic definitions.
  • Week 7 (3 Dec 2017): Information theory: applications.
  • Week 8 (10 Dec 2017): Information theory: coding.
  • Week 9 (24 Dec 2017): Chernoff bound.
  • Week 10 (31 Dec 2017): Coding theory: basic notions.
  • Week 11 (7 Jan 2018): Coding theory: some codes.
  • Week 12 (14 Jan 2018): Linear programming.
  • Week 13 (21 Jan 2018): Bonus questions and open discussion.

Bonus sheets:

Possible topics for final assignment (other topics are welcome):

  • Fourier analysis:
    • Friedgut’s junta theorem and applications or related results.
    • $p$-biased analysis and applications, for example the Friedgut–Kalai sharp threshold theorem.
    • Gaussian space, the invariance principle, and Majority is Stablest.
  • Information theory:
    • Pinsker’s inequality and applications.
    • Lower bounds in communication complexity.
    • Proof of the parallel repetition theorem due to Ankit Garg and Mark Braverman.
  • Concentration of measure and large deviation bounds:
    • Martingales, Azuma’s inequality, and McDiarmid’s inequality.
    • Martingales per se (for example, the optional stopping theorem).
  • Coding theory:
    • Efficient decoding algorithms.
    • List decoding.
    • Applications in theory of computation.
  • Linear programming:
    • Proof of strong duality via Farkas’ lemma.
    • Simplex algorithm (and another proof of strong duality).
    • Separation oracles.
    • Applications to approximation algorithms.
    • Semidefinite programming.
  • Approximation theory:
    • Proof of Markov’s inequality.
    • Other applications.
  • Algorithms in number theory:
    • Primality testing.
    • Fast integer multiplication.
    • Fast matrix multiplication.
    • Integer factorization.
    • Polynomial factorization.
  • Expander graphs:
    • Basic definitions, (double-sided) Cheeger’s inequality, Alon–Boppana.
    • Applications, for example Bourgain’s embedding theorem and its tightness.