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Whether we are interested in linear, quadratic or general nonlinear programming, interior-point methods are setting today's standard in numerical optimization. We explore the basic ideas and underlying subproblems of those methods, specify a typical algorithm and identify what its different tasks are. Numerical issues are discussed. Host: DDMA Data Sciences Summer School - Katharine Chartrand |