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This lecture covers the fundamentals of optimization in geometric computing, focusing on the concept of making a geometric object stand by finding the best modification efficiently through unconstrained optimization. Topics include derivative checks, convergence to local minimum, choosing a step size, and line search algorithms like Armijo, Wolfe, and Strong Wolfe conditions.
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