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We present an algorithm for the vertex cover problem by combining the LP relaxation and the random edge-reductions. The algorithm has the expected approximation ratio of 1.344.
In this talk, a distributed stochastic gradient (SG) algorithm is proposed where the estimators are aimed to collectively estimate an unknown time-invariant parameter from a set of noisy measurements ...
In this talk, we consider a distributed interval optimization problem (DIOP) with uncertainties, whose global function is formed by local convex interval functions. In seeking Pareto solutions for dis...
Unlike traditional robust optimization, personalized optimization aims to find the values of control variables that yield the optimal value of the objective function for given values of environmental ...
In this work, we mainly investigate the problem that minimizes the price function such that the valuation function exceeds a required threshold in submodular cover problem, where the price function is...
This talk concerns the nonsmooth distributed optimization problem via multi-agent network with the coupled equality and inequality constraints. The considered global optimization problem is to minimiz...
The aim of ALENEX is to provide a forum for the presentation of original research in the design, implementation, and experimental evaluation of algorithms and data structures. Typical submissions will...

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