First-Order Methods for Fast Feasibility Pursuit of Non-convex QCQPs

IEEE Transactions on Signal Processing（2017）

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摘要

Quadratically constrained quadratic programming (QCQP) is NP-hard in its general non-convex form, yet it frequently arises in various engineering applications. Several polynomial-time approximation algorithms exist for non-convex QCQP problems (QCQPs), but their success hinges upon the ability to find at least one feasible point-which is also hard for a general problem instance. In this paper, we ...

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关键词

Optimization,Signal processing algorithms,Convergence,Approximation algorithms,Complexity theory,Standards,Memory management

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