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Large Deviations

Course 0000005635 in WS 2022/3

General Data

Course Type lecture
Semester Weekly Hours 2 SWS
Organisational Unit Department of Mathematics
Lecturers Nina Gantert
Dates Wed, 10:15–11:45, BC2 BC2 3.1.08

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks Large deviation theory is a part of probability theory which deals with the description of "unlikely" events and determines how fast their probabilities decay. This turns out to be crucial to study the integrals of exponential functionals of sums of random variables, which come up in many different contexts. Large deviation theory finds applications in ergodic theory, information theory and statistical physics. The course will treat large deviations for i.i.d. sequences and Markov chains, large deviations for empirical measures and for sample paths and the Gibbs conditioning principle.
Links E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

WS 2021/2 Large Deviations Gantert, N. Wed, 08:30–10:00, BC2 BC2 3.5.06
WS 2020/1 Large Deviations Bäumler, J. Gantert, N. Wed, 08:30–10:00, virtuell
WS 2018/9 Large Deviations Berger Steiger, N. Wed, 08:15–09:45, BC2 BC2 3.5.06
Thu, 14:15–15:45, BC1 BC1 2.02.01
WS 2017/8 Large Deviations Berger Steiger, N.
WS 2016/7 Large Deviations Gantert, N.
WS 2015/6 Large Deviations Berger Steiger, N.
WS 2014/5 Large Deviations Gantert, N.
WS 2013/4 Large Deviations Berger Steiger, N.
WS 2012/3 Large Deviations Rolles, S.
WS 2011/2 Large Deviations Gantert, N.
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