Bertsekas - Convex Optimization Algorithms

<aside> 📖 Ch1 - principle characteristics of some convex optimization problems. [Lagrange duality theory, Fenchel duality theory] Ch2 - algorithms for differentiable optimization. ? Ch3 - subgradient methods and nondifferentiable cost functions. ? Ch4 - polyhedral approximation methods, including outer linearization and inner linearization. ! Ch5 - proximal algorithms, its combination with the polyhedral approximation and its duality. Ch6 - supplements, closed with a discussion of interior point methods.

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Duality? pair of primal and dual problems; qualitatively algorithm-oriented type of duality.

• nonlinear programming非线性规划 classical differentiable nonconvex optimization[ Kuhn-Tucker theory, Newton-like and conjugate direction methods拟牛顿法|共轭方向法, interitor point, penalty罚函数法, augmented Lagrangian methods ]