ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...

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for solving distributed optimization to minimize a sum of smooth and strongly convex local objective functions over directed graphs. The proposed method integrates the convex combination, row- and ...

This file provides functions and modules that construct shapes from a list of cross sections ... The "tangent" method generally produces good results when connecting a discrete polygon to a convex, ...

There are two procedures for applying the method of conjugate gradients to the problem of minimizing a convex, nonlinear function: the “continued” method, and the “restarted” method in which all the ...

of convexity and duality in locally convex spaces, of extended mean value inequalities in absence of differentiability, of metric regularity, of constrained optimization problems. The second volume is ...

Michigan Institute for Data and AI in Society, University of Michigan, 500 Church Street, Suite 600, Ann Arbor, Michigan 48109-1042, United States ...

MIT economists Arnaud Costinot and Iván Werning show that permanent tariffs can reduce trade deficits if imports behave like ...

Thousands of people signed up to tackle the 38th annual Convex End-to-End, which was held this year in support of Age Concern, the Bermuda Audubon Society, the Bermuda Red Cross, the Duke of ...

A random variable is one whose value is unknown or a function that assigns values to ... could be the resulting outcome as seen in the example of the dice. Random variables can be assigned in ...