A gradient method using conic or quadratic models to generate approximately optimal stepsizes, with convergence analysis and comparisons to CGDESCENT and CGOPT.
Some unconstrained optimization methods, In Applied Mathematics
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Survey classifying 78 joint OFDM-RIS optimization papers into convex relaxation, heuristics, deep learning, and foundation model paradigms, with synthesis showing ML methods achieve near model-based spectral efficiency at much higher speed.
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