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The time complexity of an algorithmic problem, i.e., the membership problem in a subset (Xsubseteq S) is the minimum of (T_{mathcal A}) for all algorithms (mathcal A) solving the problem, i.e., computing the indicator function of X.
A solving strategy that integrates model relaxation, solver selection, and tube-pass scheme initialization is proposed.
A solving strategy incorporating model decomposition, model relaxation and case initialization is proposed to find a feasible solution.
A solving of more advanced fractional differential equations on time scales requires an introduction of analogues of various special functions utilized in the continuous fractional calculus, e.g., a dynamic Mittag-Leffler function E η, β λ ( t, s ) = ∑ j = 0 ∞ λ j h ˆ η j + β − 1 ( t, s ) (see, e.g., [2, 10] and [12]).
A solving algorithm cubic of the initial data size is suggested that finds the exact conditional (refer to Section 2.5) global minimum under no gene transfers; that is, in this case the model is also exactly solvable.
I wasn't a solving prodigy in any way, but I could usually work out two or three clues in the Telegraph puzzle, sitting in the back of my parents' car while we were out shopping.
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It's a solved problem.
"I really consider autonomous driving a solved problem," he said.
We feel this is a solved problem.
It is kind of a solved problem.
Getting genotypes is in a way a solved problem.
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