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An optimal control theory for accelerated optimization

Published: 2019/02/24, Updated: 2019/05/19
  • Isaac Ross
  • Categories Convex and Nonsmooth Optimization, Unconstrained Optimization Tags accelerated newton's method, control lyapunov function, lie derivative, nesterov's accelerated gradient method, polyak's heavy ball method, riemannian metric, transversality mapping principle Short URL: https://optimization-online.org/?p=15676

    Accelerated optimization algorithms can be generated using a double-integrator model for the search dynamics imbedded in an optimal control problem.

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    alternating direction method of multipliers approximation algorithms augmented lagrangian method bilevel optimization Branch-and-Bound branch-and-cut chance constraints column generation combinatorial optimization complexity compressed sensing conic optimization convex optimization cutting planes decomposition derivative-free optimization distributionally robust optimization duality dynamic programming first-order methods global convergence global optimization heuristics integer programming interior point methods large-scale optimization linear programming machine learning mixed-integer linear programming mixed-integer nonlinear programming mixed-integer programming nonconvex optimization nonlinear optimization nonlinear programming nonsmooth optimization optimal control optimization proximal point algorithm quadratic programming robust optimization semidefinite programming stochastic optimization stochastic programming trust-region methods unconstrained optimization

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