Bare Knuckle (Vegas Top Guns, Book 5) by Katie Porter

By Katie Porter

Skin deep isn't deep enough.

After a near-fatal airplane crash, fighter pilot Captain Eric "Kisser" Donaghue is a replaced guy. via day he labors to regain his self assurance within the cockpit. by means of evening he moonlights as an off-Strip boxer, struggling with for prize cash to pay for his more youthful brother's 3rd stint in rehab.

In the hoop, not anyone cares he as soon as had a face that introduced one thousand one-night stands-and neither does Eric. He's basically there to win. but he can't take his eyes off the recent ring woman, a glitz-meets-pageant-queen imaginative and prescient of blonde perfection.

Down on her good fortune yet now not fairly out, Vegas showgirl Trish Monroe lives for the highlight. The scarred, steely-eyed loner who stares at her from his nook of the hoop offers Trish an additional cause to strut her stuff.

Curiosity and the temptation of a no-strings stable time convey them jointly. the invention in their mystery fetishes-she loves to blow their own horns, he loves to watch-turns mere sexual chemistry right into a fiery exploration of matched passions. They're a normal healthy. belief in love, notwithstanding, is tougher to earn than belief in mattress, in particular while this good looks and beast cover even from themselves.

Warning: This booklet encompasses a Sin City-style attractiveness and the Beast love tale, plenty of naughty pix and vids, adrenaline-pumped base leaping, and a collection of "very" vital be aware playing cards. Oh, and as continuously, a really scorching fighter pilot.

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Extra info for Bare Knuckle (Vegas Top Guns, Book 5)

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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 [126]. 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.

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