Publication | Closed Access
A Gradient Projection Algorithm for Relaxation Methods
39
Citations
3
References
1983
Year
Numerical AnalysisArtificial IntelligenceMathematical ProgrammingEngineeringMachine LearningVariational AnalysisConstrained OptimizationSemidefinite ProgrammingConvex HullEnergy MinimizationGradient ProjectionDerivative-free OptimizationComputational GeometryApproximation TheoryVariational InequalitiesContinuous OptimizationGradient Projection AlgorithmInverse ProblemsComputer ScienceConic OptimizationConvex Optimization
We consider a particular problem which arises when apply-ing the method of gradient projection for solving constrained optimiza-tion and finite dimensional variational inequalities on the convex set formed by the convex hull of the standard basis unit vectors. The method is especially important for relaxation labeling techniques applied to problems in artificial intelligence. Zoutendijk's method for finding feasible directions, which is relatively complicated in general situations, yields a very simple finite algorithm for this problem. We present an extremely simple algorithm for performing the gradient projection and an independent verification of its correctness.
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