Seminar in Applied Probability and Stochastic Processes

2-0-4 units · Graduate

Doctoral student seminar covering current topics in applied probability and stochastic processes.

Spring 2006 · Special Seminar in Applied Probability and Stochastic Processes

This seminar is intended for doctoral students and discusses topics in applied probability. This semester includes a variety of fields, namely statistical physics (local weak convergence and correlation decay), artificial intelligence (belief propagation algorithms), computer science (random K-SAT problem, coloring, average case complexity) and electrical engineering (low density parity check (LDPC) codes).

Readings

SES #: 1 · READINGS: Frieze, Alan, and Nicholas C. Wormald. “Random k-SAT: A Tight Threshold for Moderately Growing k.” Combinatorica 25, no. 3 (2005): 297-305. ( PDF ) ↗
Reading assignment
SES #: 2 · READINGS: Achlioptas, Dimitris, and Assaf Naor. “The Two Possible Values of the Chromatic Number of a Random Graph.” Annals of Mathematics 162, no. 3 (2005): 1335-1351. ( PDF ) ↗
Reading assignment
SES #: 3 · READINGS: Kelly, F. P. “Stochastic Models of Computer Communication Systems (in A Symposium on Stochastic Networks).” Journal of the Royal Statistical Society. Series B (Methodological) 47, no. 3 (1985): 379-395.
Reading assignment
SES #: 4 · READINGS: Weitz, D. “Counting Independent Sets up to the Tree Threshold.” ( PDF ) ↗
Reading assignment
SES #: 5 · READINGS: Aldous, D., and J. Steele. “The Objective Method: Probabilistic Combinatorial Optimization and Local Weak Convergence.” In Probability on Discrete Structures . Edited by Harry Kesten. New York, NY: Springer-Verlag, 2003. ISBN: 3540008454. ( PS ) ↗
Reading assignment
SES #: 6 · READINGS: Gamarnik, David, Tomasz Nowicki, and Grzegorz Swirszcz. “ Maximum Weight Independent Sets and Matchings in Sparse Random Graphs. Exact Results Using the Local Weak Convergence Method .” Random Structures and Algorithms 28, no. 1 (2006): 76-106. ↗
Reading assignment
SES #: 7-8 · READINGS: Wainwright, M. J., and M. I. Jordan. “Graphical Models, Exponential Families and Variational Inference.” UC Berkeley, Dept. of Statistics, Technical Report 649 (2003). ( PS - 1.7 MB ) ↗
Reading assignment
SES #: 9 · READINGS: Bayati, M., D. Shah, and M. Sharma. “Maximum Weight Matching via Max-product Belief Propagation.” International Symposium on Information Theory , Proceedings (2005): 1763-1767. ↗
Reading assignment
SES #: 10 · READINGS: Richardson, T., and R. Urbanke. Modern Coding Theory . Cambridge, UK: Cambridge University Press, 2006, chapters 1 and 2. (Forthcoming) ↗
Reading assignment

Prerequisites & course information

Prereq: 6.3702 G (Fall) Not offered regularly; consult department 2-0-4 units Can be repeated for credit.

Sources

Course catalogue ↗2026–2027
MIT OpenCourseWare ↗Spring 2006
MIT OCW readings ↗
MIT OCW syllabus ↗
Historical MIT OpenCourseWare offering. Named reading entries and schedule topics are automatically extracted from the linked source pages.