� Solution to many practical problems is defined by the satisfaction an overconstrained system of (possibly nonlinear) equations. � Even if the equations are linear, the number of variables involved is usually too high for one to apply a naïve solution such as least square. � Relaxation

– Correspondences between a reference and input image. – No a priori pose information. • Output: – A mapping F from model to input image.

We present a method to determine optimal solutions to geometric correspondence problems. Using pair-wise constraints in combination with graph methods we show how to efficiently find optimal correspon-dences.- Handles large rates of outliers.- Competetive run times.

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The problem of selecting a consistent initial guess for the full waveform to-mography of a semi-infinite elastic solid is considered in the framework

● System model

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zed by an ordinary differential equation: x(t) = f(x(t); u(t); d(t)) x(0) = x 0 u(t) 2 U d(t) 2 D (1) To prevent technical problems, we introduce the following assumption: Assumption 1 f is Lipschitz continuous in x and continuous in u and d. u and d are piecewise continuous as functions

multi-dimensional diffusion on R n: where

• Whether a new product meets its BOM cost target and can deliver an acceptable financial contribution is often down to chance and subject to an element of manipulation. • To mitigate this problem we develop and demonstrate a theoretical method to notionally hedge and thereby value the stochastic