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Foundations of Data Analysis (MA4800)

News

  • The exam for MA4800 Foundations of Data Analysis will take place on August 2, 2018 in room MW 2001, Rudolf-Diesel-Hörsaal (5510.02.001), from 1:30 - 3:00 PM. There are no support materials allowed for the exam.
  • The tutorial sessions begin the week of April 16, 2018.
  • The end-of-the-semester exam will take place on August 2, 2018, from 1:30 - 3:00 PM. The locations will be announced in due course.
  • Due to the May Day holiday, students who are in the Tuesday tutuorial session are encouraged to attend one of the other sessions.
  • Due to the Pentecost Holiday break, there will be no lecture on Tuesday, May 22, 2018 and the tutuorial sessions during the week of May 21, 2018, are cancelled.
  • A new version of the lecture notes has been uploaded with corrections of typos until end of Chapter 5

Organization

  • Lectures (4 SWS)
  • Tutorial Sessions (2 SWS)
    • Tutorial Session 1 (Dr. Christian Ludwig)
      • Time: Mondays, 10:00 - 12:00
      • Location: MI 01.09.014
    • Tutorial Session 2 (M.Sc. Alvaro De Diego)
      • Time: Mondays, 10:00 - 12:00
      • Location: MI 02.07.023
    • Tutorial Session 3 (M.Sc. Johannes Maly)
      • Time: Mondays, 16:00 - 17:30
      • Location: MI 00.09.022
    • Tutorial Session 4 (Dr. Christian Ludwig)
      • Time: Mondays, 16:00 - 17:30
      • Location: MI 03.08.011
    • Tutorial Session 5 (M.Sc. Alvaro De Diego)
      • Time: Wednesdays, 16:00 - 17:30
      • Location: MI 02.08.011
    • Tutorial Session 6 (Dipl.-Math. Sandro Belz)
      • Time: Tuesdays, 16:00 - 17:30
      • Location: MI 02.08.011

Lecture Slides

Slides of the lecture

Lecture Notes

Lecture Notes

Problem Sets

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).