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WebBackground and optimization basics; 2. Convex sets and functions; 3. Canonical convex optimization problems (LP, QP, SDP); 4. Second-order methods (unconstrained and constrained optimization); 5. First-order methods (gradient, subgradient, conjugate gradient); 6. Alternating Direction Method of Multipliers. 18 4 The case of a convex cost … WebAbout this book. This book discusses unconstrained optimization with R—a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi … fiscal year c corporation due date
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