Maijian Qian

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We propose an optimization approach ~o the estimation a simple closed curve describing the boundary of an object represented in an image. This problem arises in a variety of applications, such as template matching schemes for medical image registration. A regularized optimization formulation with an objective function that measures the normalized image(More)
In previous work, the authors provided a foundation for the theory of variable metric proximal point algorithms in Hilbert space. In that work conditions are developed for global, linear, and super–linear convergence. This paper focuses attention on two matrix secant updating strategies for the finite dimensional case. These are the Broyden and BFGS(More)
Let C be a nonempty closed subset of the real normed linear space X. In this paper we determine the extent to which formulas for the Clarke subdifferential of the distance for C, de(x) := inf I/Y.rll, be< which are valid when C is convex, remain valid when C is not convex. The assumption of subdifferential regularity for d, plays an important role. When x 4(More)
This paper proposes an implementable proximal quasi-Newton method for minimizing a nondi erentiable convex function f in < n . The method is based on Rockafellar's proximal point algorithm and a cutting-plane technique. At each step, we use an approximate proximal point p a (x k ) of x k to de ne a v k 2 @ k f(p a (x k )) with k kv k k; where is a constant.(More)
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