Explores strategic decisions for Smart City policy-makers, covering technological, financial, political, and social aspects.
Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Covers optimization methods without constraints, including gradient and line search in the quadratic case.
Covers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.
Explores Stochastic Gradient Descent and Mean Field Analysis in two-layer neural networks, emphasizing their iterative processes and mathematical foundations.
Covers the Runge Kutta method and its application to optimal control and neural networks.
Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
