By Stephanie Bond
The hardheaded Armstrong brothers are made up our minds to rebuild their tornado-ravaged native land within the Georgia mountains. They've bought the capacity, they've bought the manpower...what they want are girls! so that they position an advert in a Northern newspaper and look ahead to the women to arrive....
Sensible but attractive heart brother Kendall Armstrong penned that advert himself--but there's only one girl he quite desires to resolution the call....
Civil engineer Amy Bradshaw--Kendall's ex-fiancée--fled Sweetness years in the past, taking a worthwhile keepsake together with her. She's again now...but simply on a qualified point. Really.
Little does she understand that outdated flames continuously burn the hottest....
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Additional info for Baby, Come Home (Southern Roads, Book 2)
12) to get z k . Adopting such an iterative approach presupposes that maximizing H(z k−1 , z) is simpler than maximizing f (z) itself. This is the case with the EM algorithms. Sequential Optimization 31 One of the most useful and easily proved facts about the KullbackLeibler distance is contained in the following lemma. 1 For nonnegative vectors x and z, with z+ = have x+ KL(x, z) = KL(x+ , z+ ) + KL(x, z). 13) This lemma can be extended to obtain the following useful identity; we simplify the notation by setting b(z) = b(x, z).
3 Proximal Minimization . . . . . . . . . . . . . . . . . 4 The IPA . . . . . . . . . . . . . . . . . . . . . . . . . 25 26 27 27 28 28 28 29 29 30 31 31 32 33 34 The Landweber and projected Landweber algorithms, the SMART and the EMML are all examples of sequential optimization methods. Perhaps the best known examples of sequential optimization are the sequential unconstrained minimization (SUM) methods . Auxiliary-function algorithms, a broad subclass of sequential optimization methods, provide a unifying framework for these and many other iterative algorithms.
6 The Lagrangian in Convex Programming . . . . . . . . 7 Inﬁmal Convolution . . . . . . . . . . . . . . . . . . . 8 Moreau’s Proximity-Function Method . . . . . . . . . Basic Facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 35 36 36 36 39 39 39 40 40 40 41 41 42 42 43 Barrier-function and penalty-function methods are the best known examples of sequential optimization. In their usual formulations neither ﬁts into the AF class of algorithms.