Advanced Topics in Systems, Control and Learning 1 (048715)
Monte Carlo Methods for Computation and Optimization
Nahum Shimkin
Spring 2015
Syllabus (pdf)
2015 Lecture Notes:
§ Lecture 1 : Introduction
§ Lecture 2: Random Variable Generation
§ Lecture 3: Variance Reduction Methods, I
§ Lecture 4: Importance Sampling
§ Lecture 5: Sequetial Importance Sampling; Slides for section 5.3: Particle Filters
§ Lecture 6: Markov Chain Monte Carlo
§ Lecture 7: Some Topics in Brief
Homework:
· Problem Set 1 Submission April 29.
· Problem Set 2 (parts a+b). Submission June 3
· Problem Set 3 Submission June 24
Homework and
Assignment Grades
Slides of Student Presentations:
· Ariel: Simulated Annealing for Constrained Global Optimization
· Ayal: N-grams in MC Tree Search
· Gal: Modern Floor Planning with Simulated Annealing
· Nir: Reversible Jump Markov Chain Monte Carlo
· Niv: MC Simulation of Security Prices
· Oron: Computing Approximate Nash Equilibria
· Noam: Cross Entropy for Monte Carlo Trees Search