Sinposis

"The mathematical definitions, notations, and relations from linear algebra, geometry, and calculus used in optimization.Optimization algorithms, covering one-dimensional search, randomized search, and gradient, Newton, conjugate direction, and quasi-Newton methodsLinear programming methods, covering the simplex algorithm, interior point methods, and duality.Nonlinear constrained optimization, covering theory and algorithms, convex optimization, and Lagrangian duality.Applications of optimization in machine learning, including neural network training, classification, stochastic gradient descent, linear regression, logistic regression, support vector machines, and clustering."