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Online Convex Programming and Generalized Infinitesimal Gradient Ascent
, 2003
"... Convex programming involves a convex set F R and a convex function c : F ! R. The goal of convex programming is to nd a point in F which minimizes c. In this paper, we introduce online convex programming. In online convex programming, the convex set is known in advance, but in each step of some ..."
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Cited by 183 (4 self)
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Convex programming involves a convex set F R and a convex function c : F ! R. The goal of convex programming is to nd a point in F which minimizes c. In this paper, we introduce online convex programming. In online convex programming, the convex set is known in advance, but in each step of some repeated optimization problem, one must select a point in F before seeing the cost function for that step. This can be used to model factory production, farm production, and many other industrial optimization problems where one is unaware of the value of the items produced until they have already been constructed. We introduce an algorithm for this domain, apply it to repeated games, and show that it is really a generalization of in nitesimal gradient ascent, and the results here imply that generalized in nitesimal gradient ascent (GIGA) is universally consistent.
Separation and weak König’s lemma
 Journal of Symbolic Logic
, 1999
"... investigating the strength of set existence axioms needed for separable Banach space theory. We show that the separation theorem foropenconvexsetsisequivalenttoWKL0 over RCA0. Weshow that the separation theorem for separably closed convex sets is equivalent to ACA0 over RCA0. Our strategy for provin ..."
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Cited by 5 (2 self)
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investigating the strength of set existence axioms needed for separable Banach space theory. We show that the separation theorem foropenconvexsetsisequivalenttoWKL0 over RCA0. Weshow that the separation theorem for separably closed convex sets is equivalent to ACA0 over RCA0. Our strategy for proving these geometrical Hahn–Banach theorems is to reduce to the finitedimensional case by means of a compactness argument. 1.