ACN6347 - Intelligent Systems Analysis

ACN 6347 (HCS 6347) Intelligent Systems Analysis (3 semester credit hours) Mathematical tools for investigating the asymptotic behavior of both deterministic and stochastic nonlinear optimization methods for machine learning algorithms. Topics include: artificial neural network architectures, Lyapunov stability theory, nonlinear optimization theory, stochastic approximation theory, and Monte Carlo Markov Chain methods such as the Metropolis-Hastings algorithm. Emphasizes development of advanced analytic skills and mathematical reasoning abilities. Prerequisites: (Linear algebra, multivariable calculus, and STAT 3341 or equivalent) and BBSC majors only and department consent required. (3-0) T