Algorithms are everywhere. They detail the specific instructions that computers need to carry out tasks, from self-driving vehicles to recommendation systems. The ability of algorithms to automate and engineer systems that reason has made them a cornerstone of contemporary society. Although full neural network models can also serve as task solvers and utilize additional information from data to tailor existing algorithms to real-world problems, a trade-off is that these systems sacrifice generalization ability.
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