Hi, In have a question about the HPX smart executors talked about in this article https://arxiv.org/pdf/1711.01519.pdf . I'm not sure to understand the way the way the data is generated. As an example, let's say I want to optimize a matrix multiplication task. The executor will use a logistic regression to optimize the task but has the logistic regression already been trained with previous data from a large data set? Or does the executor generate data from the task I give it and then it trains a logistic regression using that data which would mean that the regression is perfectly optimized for the given task but take some time to train. Thank you very much,
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