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By using the primal SVM technique [ 21], we formulate the CRanker classification model as (5) min β, θ β T K β + c 1 ∑ i = 1 l θ i ⋅ max 0, 1 - y i K i T β p - c 2 ∑ i = 1 l θ i s.t.
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Based on the instantaneous channel measurement and the experiential channel state transition probability anticipation, the relay selection problem is solved by using the primal-dual index heuristic algorithm with switching costs of relay reselection being considered.
We show theoretically that our algorithm converges to the optimal solution of the primal problem by using the knowledge of stochastic programming.
They show theoretically that the algorithm converges to the optimal solution of the primal problem by using the knowledge of stochastic programming.
Instead of working on the primal space, this method performs a dual step on the dual space by using the dual gap function.
Sigma uses the primal-dual interior point NLP method implemented in the Ipopt library (Wachter and Biegler, 2006).
In [55], the authors obtained optimal solution to their RA problem by using a primal-dual decomposition method whereby the overall problem is decomposed into individual power allocation sub-problems and solved for every decision variable pair.
By using primal decomposition, P C can be divided into two subproblems.
Since the primal problem in (38) is convex, strong duality holds, and the dual problem can be solved by an iterative manner using the gradient projection method [24].
We solve model (28) by using recently developed first-order primal-dual algorithm (see, e.g., [24 26]).
To confirm this result, solve the primal optimization problem and resilience problem using the fixed modulation pairs of (PK, SERS) and (PK, G6PDH).
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