AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020, pp. 199-208, 2020.

Cited by: 0|Bibtex|Views227|DOI:https://doi.org/10.1145/3397271.3401082
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

Modelling feature interactions is key in Click-Through Rate (CTR) predictions. State-of-the-art models usually include explicit feature interactions to better model non-linearity in a deep network, but enumerating all feature combinations of high orders is not efficient and brings challenges to network optimization. In this work, we use A...More

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