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Idiom
Problem is thirty.
If a problem is 30, the problem is the person who sits 30 cm from the computer screen.
Exact(60)
The problem is reformulated in terms of reinforcement learning.
The problem is reformulated in dimension-free quantities.
The original nonconvex problem is reformulated as two reduced dimension semi-definite programming (SDP) problems.
The problem is reformulated in terms of a constrained nonlinear optimization problem.
The problem is reformulated as an MILP after exact linearization of structural constraints.
The problem is reformulated to a minimization problem in one dimension.
The minimax optimization problem is reformulated to a nonlinear programming problem with constraints.
Through an application of Karush-Kuhn-Tucker conditions, the problem is reformulated as a convex one.
The topology optimization problem is reformulated as a volume minimization problem having probabilistic displacement constraints using the performance measure approach.
Based on these results, the optimal control problem is reformulated allowing online implementation via dynamic real-time optimization.
Furthermore, the optimization problem is reformulated as a convex problem using semidefinite relaxation (SDR) method to be solved more efficiently.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com