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Compositional ADAM: An Adaptive Compositional Solver - MaRDI portal

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Compositional ADAM: An Adaptive Compositional Solver

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Publication:6334481

arXiv2002.03755MaRDI QIDQ6334481

Author name not available (Why is that?)

Publication date: 10 February 2020

Abstract: In this paper, we present C-ADAM, the first adaptive solver for compositional problems involving a non-linear functional nesting of expected values. We proof that C-ADAM converges to a stationary point in mathcalO(delta−2.25) with delta being a precision parameter. Moreover, we demonstrate the importance of our results by bridging, for the first time, model-agnostic meta-learning (MAML) and compositional optimisation showing fastest known rates for deep network adaptation to-date. Finally, we validate our findings in a set of experiments from portfolio optimisation and meta-learning. Our results manifest significant sample complexity reductions compared to both standard and compositional solvers.












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