MATH589B
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MATH589B - Algorithms of Applied Mathematics II
Course ID
041863
Course Description
Least squares problem. Unconstrained Optimization: gradient descent with backtracking, Newton method; constrained optimization: primal-dual Newton, interior point methods; linear programming. Inference and Learning Algorithms: sampling algorithms, Monte-Carlo method, importance sampling, stochastic optimization; regression, classification, clustering. Other topics as chosen by the instructor.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Course Attributes
CE - CL (Cross Listed), GIDP - APPL (Applied Mathematics)
Course Requisites
Math 589A
Cross Listed Courses
May be convened with
Component
Lecture
Optional Component
No