A new Ideal direction is proposed for Gradient Sampling that avoids quadratic programs at each step, satisfies Armijo, and preserves global convergence for nonsmooth nonconvex problems.
Master’s thesis, New York University (2010)
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A Gradient Sampling method based on Ideal direction for solving nonsmooth nonconvex optimization problems: convergence analysis and numerical experiments
A new Ideal direction is proposed for Gradient Sampling that avoids quadratic programs at each step, satisfies Armijo, and preserves global convergence for nonsmooth nonconvex problems.