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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.
Covers the Runge Kutta method and its application to optimal control and neural networks.
Covers advanced numerical analysis topics including deep neural networks and optimization methods.
Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
Covers the Finite Element Method, discussing the derivation of the equation of motion and exploring mass and stiffness matrices.
Explores strategic decisions for Smart City policy-makers, covering technological, financial, political, and social aspects.
Explores the physics of a cylinder balancing on a step and a counterweight system with a rotating vertical cylinder.
