BannerHauptseite TUMHauptseite LehrstuhlMathematik SchriftzugHauptseite LehrstuhlHauptseite Fakultät

Foundations of Data Analysis (MA4800)

News

  • The exercise sessions will start during the week of May 8, 2017.
  • Because of the Whitsun Holidays there will be no exercise sessions on Monday, June 5, 2017 and on Tuesday, June 6, 2017. There will also be no lecture on Tuesday, June 6, 2017.

Organization

Lecture Slides

25 April 2017
26 April 2017
2 May 2017
3 May 2017
9 May 2017
10 May 2017
16 May 2017
17 May 2017
24 May 2017
30 May 2017
31 May 2017
7 June 2017
13 June 2017
14 June 2017
20 June 2017
21 June 2017
27 June 2017
28 June 2017
05 July 2017
11 July 2017
12 July 2017
18 July 2017

Lecture Notes

Lecture Notes

Problem Sets

Problem Set 1
Problem Set 2 (countries_data.txt) (MATLAB Codes)
Problem Set 3 (Bird_Data)
Problem Set 4 (Poly_Data) (MATLAB Codes)
Problem Set 5
Problem Set 6
Problem Set 7 (MATLAB Codes)
Problem Set 8
Problem Set 9
Problem Set 10
Problem Set 11 (MATLAB Codes)
Solution Proposals

Literature

  • A. Bandeira, Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science, http://www.cims.nyu.edu/~bandeira/TenLecturesFortyTwoProblems.pdf
  • G. Bennett, Probability inequalities for the sum of independent random variables, J. Amer. Statist. Assoc. 57 (1962), 33-45.
  • H. Chernoff, A measure of asymptotic efficiency of tests of a hypothesis based on the sum of observations, Ann. Math. Statist. 23 (1952), 49-507.
  • G. Grimmett and D. Stirzaker, Probability and Random Processes, third ed., Oxford University Press, New York, 2001.
  • W. Hackbusch, Tensor Spaces and Numerical Tensor Calculus, Berlin: Springer, 2012 (English).
  • R. A. Horn and Ch. R. Johnson, Matrix Analysis, 2nd ed., Cambridge University Press, 2013 (English).
  • J. Hopcroft and R. Kannan, Computer Science Theory for the Information Age, https://www.cs.cmu.edu/~venkatg/teaching/CStheory-infoage/book-chapter-4.pdf, 2012.
  • T. Hagerup and C. Rüb, A guided tour of Chernoff bounds, Inform. Process. Lett. 33 (1990), No. 6, 305-308.
  • I.T. Jolliffe, Principal Component Analysis, 2nd ed., Springer, 2002 (English).
  • G. Kemper, Lineare Algebra für Informatik, Lecture Notes, 2017
  • M. Mazeika, The singular value decomposition and low rank approximation, http://math.uchicago.edu/~may/REU2016/REUPapers/Mazeika.pdf, 2016.
  • C. McDiarmid, Concentration, Probabilistic methods for algorithmic discrete mathematics, Algorithms Combin., Vol. 16, Springer, 1998, 195-248.
  • L. Mirsky, Symmetric gauge functions and unitarily invariant norms, The Quarterly Journal of Mathematics 11 (1960), No. 1, 50.
  • S. Ross, Introduction to Probability Models, nineth ed., Academic Press, 2006.
  • S. Varadhan, Large Deviations and Applications, École d'Été de Probabilités de Saint-Flour XV-XVII, 1985-87, Lecture Notes in Math., Vol. 1362, Springer, 1988, 1-49.
  • R. Vershynin, High dimensional probability, https://www.math.uci.edu/~rvershyn/papers/HDP-book/HDP-book.html, 2017.
  • H. Weyl , Das asymptotische Verteilungsgesetz der Eigenwerte linearer partieller Differentialgleichungen (mit einer Anwendung auf die Theorie der Hohlraumstrahlung)., Math. Ann. 71 (1912), 441-479 (German).