Learning with Differentiable Algorithms. (arXiv:2209.00616v1 [cs.LG])

Classic algorithms and machine learning systems like neural networks are both
abundant in everyday life. While classic computer science algorithms are
suitable for precise execution of exactly defined tasks such as finding the
shortest path in a large graph, neural networks allow learning from data to
predict the most likely answer in more complex tasks such as image
classification, which cannot be reduced to an exact algorithm. To get the best
of both worlds, this thesis explores combining both concepts …

algorithms arxiv learning