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David Sommer

Bio: David Sommer is an academic researcher. The author has contributed to research in topics: Rank (linear algebra) & Tensor (intrinsic definition). The author has co-authored 1 publications.

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TL;DR: In this paper, a low-rank tensor train (TT) decomposition based on the Dirac-Frenkel variational principle is proposed for nonlinear optimal control.
Abstract: We present a novel method to approximate optimal feedback laws for nonlinear optimal control based on low-rank tensor train (TT) decompositions. The approach is based on the Dirac-Frenkel variational principle with the modification that the optimisation uses an empirical risk. Compared to current state-of-the-art TT methods, our approach exhibits a greatly reduced computational burden while achieving comparable results. A rigorous description of the numerical scheme and demonstrations of its performance are provided.

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TL;DR: In this paper , the authors propose a solution to solve the problem of the problem: this paper ] of "uniformity" and "uncertainty" of the solution.
Abstract: ,