Importance Sampled Circuit Learning Ensembles (ISCLEs) is a novel analog circuit topology synthesis method that returns designertrustworthy circuits yet can apply to a broad range of circuit design problems including novel functionality. ISCLEs uses the machine learning technique of boosting, which does importance sampling of “weak learners” to create an overall circuit ensemble. In ISCLEs, the...

Motivated by original Skorokhod's ideas, a new topology has been deened on the space P(X) of tight probability distributions on a topological space (X;). The only topological assumption imposed on (X;) is that some countable family of continuous functions separates points of X. This new sequential topology, deened by means of a variant of the a.s. Skorokhod representation, is quite operational ...

We study the robustness of interim correlated rationalizability to perturbations of higher-order beliefs. We introduce a new metric topology on the universal type space, called uniform-weak topology, under which two types are close if they have similar first-order beliefs, attach similar probabilities to other players having similar first-order beliefs, and so on, where the degree of similarity...

(A) We consider measure preserving actions of an infinite, countable (discrete) group Γ on non-atomic standard measure spaces (X,μ), i.e., standard Borel spaces equipped with a non-atomic probability Borel measure. (All such measure spaces are isomorphic to ([0, 1], λ), where λ is Lebesgue measure.) We denote by A(Γ, X, μ) the space of such actions. If a ∈ A(Γ, X, μ) and γ ∈ Γ, we denote by γ(x...

The first part of the paper deals with general features of weak star convergence from a topological point of view. We present basic facts about weak and weak star topologies, dual spaces and representations of linear functionals as Radon measures. A special attention is payed to finitely additive measures and some results regarding the Baire sets. We prove that in a wide class of topological sp...