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The implications of Theorem 1 are discussed in Sections "Recovery of optimal primal variables" and "Dual descent algorithms".
We also discuss a stochastic optimization algorithm to determine optimal dual variables that can operate without knowledge of the channel probability distribution (Section "Dual descent algorithms").
Algorithms that find primal optimal operating points regardless of the characteristics of the set of Lagrangian maximizers are studied in Section "Dual descent algorithms".
The purpose of the primal iteration (S1) is to compute the stochastic subgradients in (S2) that are needed to implement the dual descent update in (S3).
Consider the optimization problem in (20) as well as processes p ( N ) and x ( N ) generated by the stochastic dual descent algorithm (S1)–(S1).
Throughout the article concepts are illustrated with the optimal design of a frequency division broadcast channel (Section "Frequency division broadcast channel" in "Optimal wireless system design", Section "Frequency division broadcast channel" in "Recovery of optimal primal variables", and Section "Frequency division broadcast channel" in "Dual descent algorithms").
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She develops one such alternative model by staging a fictional conversation between Beauvoir and Nigerian Igbo thinkers on the maternal ethos of the consanguineal, woman-woman, matrilineal, and dual-descent families with striking implications.
Dual coordinate descent.
In [49] a cost-sensitive SVM using randomized dual coordinate descent method (CSVM-RDCD) was proposed.
To implement dual stochastic descent for the frequency division broadcast channel we need to specify the primal iteration (S1) and the dual iteration (S2).
Another strategy for user association based on the dual coordinate descent method is derived in [11] in order to balance the network load by adopting a design criterion driven by the network utilization and proportional fairness.
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