June 5, 2024, 4:43 a.m. | Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki, Assaf Schuster

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.02187v1 Announce Type: new
Abstract: Many recent works use machine learning models to solve various complex algorithmic problems. However, these models attempt to reach a solution without considering the problem's required computational complexity, which can be detrimental to their ability to solve it correctly. In this work we investigate the effect of computational time and memory on generalization of implicit algorithmic solvers. To do so, we focus on the Differentiable Neural Computer (DNC), a general problem solver that also lets …

abstract arxiv complexity computational cs.lg however machine machine learning machine learning models planning problem solution solve type work

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