ACM 216: Markov Chains, Discrete Stochastic Processes and Applications.
Last Update: December 30, 2017Homework: Sent via email to registered students (drop the instructor an email if you are not registered yet to be added to the email list).Lecture Notes : Sent via email to registered studentsPrerequisite: ACM/EE 116 or CMS/ACM/EE 117 or instructor agreementPiazza: for all class-related discussions (in particular for Q/A).https://piazza.com/caltech/winter2018/acm216/homeSchedule: Classes are scheduled from 9:00am to 10:25am on Tuesdays and Thursdays in 105 Annenberg.Grading: Homework (5 problem sets, one every two weeks): 100%Instructor: Houman OwhadiOffice hour: Tues/Thu 10:30am-11:00 am, Steele House, 201.TAs:•Florian T. Schäfer:oOffice hour: Wednesday 4:30-5:30pmoLocation: Annenberg 106oPhone: 626 365 7384 oEmail: firstname.lastname@example.org•Robin Brown:oOffice hour: Monday 8-9pm oLocation: Annenberg 107oPhone: 301 5266178oEmail: email@example.com•Anna Winnicki:oOffice hour: Tuesday 3-4pm oLocation: Annenberg oPhone: 808-343-7200oEmail: firstname.lastname@example.orgSyllabus:Markov Chains.Computer simulation of Markov Chains.Irreducible and aperiodic Markov Chains.Stationary Distributions.Reversible Markov Chains.Markov Chain Monte Carlo.Fast Convergence of MCMC algortithms.Approximate counting.The Propp-Wilson algorithm.Sandwiching.Simulated annealing.Convergence rates.Continuous time Markov ChainsTextbooks: The lectures will not follow closely any of those textbooks (I will distribute my lecture notes), they are given here only as suggestions.•Markov Chains and Stochastic Stability (S. P. Meyn and R. L. Tweedie). Well written and comprehensive. Can be downloaded from http://probability.ca/MT/•Finite Markov Chains and Algorithmic Applications (Olle Hagstrom). This thin and inexpensive book is a nice and up-to-date introduction to Markov Chain, algorithms and applications.•Markov Chains, Gibbs Fields, Monte Carlo Simulation, and Queues (P. Bremaud).