Stochastic gradient descent with gradient estimator for categorical features

▤ Summary

The broad field of machine learning (ML) provides a wide array of techniques and methods that cover numerous situations. Such was the case with categorical variables, which are omnipresent in supply chain - for example, to represent product categories, countries of origin, payment methods, etc. Thus, a few of us decided to revisit the notion of categorical variables from a differentiable programming perspective. In order to apply recent machine learning models on such data, encoding is needed. Overall, the aim of this paper is to thoroughly consider categorical data and adapt models and optimizers to these key features.

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