On reconstructability of quadratic utility functions from the iterations in gradient methods

DOI10.1016/j.automatica.2016.01.014zbMath1335.93132arXiv1509.05500OpenAlexW2963834707MaRDI QIDQ254603

Mikael Johansson, Iman Shames, Farhad Farokhi, Michael G. Rabbat

Publication date: 8 March 2016

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.05500

zbMATH Keywords

quadratic programmingparameter identificationgradient methodsstatistical inferencedata confidentialitydata privacy

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Quadratic programming (90C20) Identification in stochastic control theory (93E12)

Related Items (3)

Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs ⋮ Distributed safe resource allocation using barrier functions ⋮ On reconstructability of quadratic utility functions from the iterations in gradient methods

Cites Work

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• On reconstructability of quadratic utility functions from the iterations in gradient methods
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• Numerical Optimization
• Convex programming in Hilbert space

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