In this paper we propose the use of damped techniques within Nonlinear Conjugate Gradient (NCG) methods. Damped techniques were introduced by Powell and recently reproposed by Al-Baali and till now, only applied in the framework of quasi--Newton methods. We extend their use to NCG methods in large...
Nonlinear Optimization
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Starting from the paper by Nash and Sofer (1990), we propose a heuristic adaptive truncation criterionfor the inner iterations within linesearch-based truncated Newton methods. Our aim is to possibly avoid ‘‘over-solving’’ of the Newton equation, based on a comparison between the predicted...
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We consider the convex quadratic linearly constrained problem with bounded variables and with huge and dense Hessian matrix that arises in many applications such as the training problem of bias support vector machines. We propose a decomposition algorithmic scheme suitable to parallel...
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