A gradient method using conic or quadratic models to generate approximately optimal stepsizes, with convergence analysis and comparisons to CGDESCENT and CGOPT.
C.: The Q-Superlinear Convergence of a Coll inear Scaling Algorithm for Unconstrained Optimization
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An Improved Gradient Method with Approximately Optimal Stepsize Based on Conic model for Unconstrained Optimization
A gradient method using conic or quadratic models to generate approximately optimal stepsizes, with convergence analysis and comparisons to CGDESCENT and CGOPT.