An efficient global algorithm for worst-case linear optimization under uncertainties based on nonlinear semidefinite relaxation.
Xiaodong DingHezhi LuoHuixian WuJianzhen LiuPublished in: Comput. Optim. Appl. (2021)
Keyphrases
- semidefinite
- worst case
- semidefinite programming
- learning algorithm
- optimization algorithm
- convex relaxation
- computational complexity
- np hard
- dynamic programming
- objective function
- complementarity problems
- linear programming
- higher dimensional
- primal dual
- optimization method
- lower bound
- convergence rate
- linear systems
- quadratic programming
- training data
- optimal solution
- finite dimensional
- machine learning