Introduction to contemporary computational culture: reproducible coding, literate programming. Monte Carlo methods: random number generation, variance reduction, numerical integration, statistical simulations. Optimization (linear search, gradient descent, Newton-Raphson, method of scoring, and their specifics in the statistical context), EM algorithm. Fundamentals of convex optimization with constraints. Prerequisites: consent of the instructor.
Section | Capacity | Class times | Login to view Instructor(s) and Location |
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LECTURE Q1
(78739) |
45 |
2025-01-06 - 2025-04-09 (MWF)
12:00 - 12:50
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Section | Capacity | Class times | Login to view Instructor(s) and Location |
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LECTURE Q1
(87117) |
40 |
2026-01-05 - 2026-04-10 (MWF)
12:00 - 12:50
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