i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender Systems

Input features play a crucial role in DNN-based recommender systems with thousands of categorical and continuous fields from users, items, contexts, and interactions. Noisy features and inappropriate embedding dimension assignments can deteriorate the performance of recommender systems and introduce...

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Veröffentlicht in:	arXiv.org 2023-11
Hauptverfasser:	Yao, Yao, Liu, Bin, He, Haoxun, Dakui Sheng, Wang, Ke, Li, Xiao, Cao, Huanhuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complexity Computer Science - Artificial Intelligence Computer Science - Information Retrieval Computer Science - Learning Embedding Feature selection Optimization Performance prediction Recommender systems Searching
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