Abstract: Data set composed of categorical features is very common in big data analysis tasks. Since categorical features are usually with a limited number of qualitative possible values, the nested ...
Abstract: When analyzing heterogeneous data comprising numerical and categorical attributes, it is common to treat the different data types separately or transform the categorical attributes to ...
Synthetic data is becoming increasingly important for accelerating the development of language models, both large and small. Despite several successful use cases, researchers also raised concerns ...
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