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I have an optimization problem that I solved with grid search using hyperopt in python. In this problem, I have some parameters and a score. I want to find the best parameters that maximize this score. Until now, I didn't see any machine learning algorithms used for solving the optimization task. For example, in classification, we define the problem and use an optimizer (like SGD) to find the best weights. Are there any ML algorithms that can learn how to solve an optimization problem?

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Optimization is a very broad field. There are many examples of applying machine learning to optimization subfields.

One example is "Learning to Optimize" which uses reinforcement learning (RL). A particular optimization algorithm is defined as a policy and RL can be used to find the best relative policy.

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