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A Survey on Dropout Methods and Experimental Verification in Recommendation

IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022

5 April 2022

Papers citing "A Survey on Dropout Methods and Experimental Verification in Recommendation"

4 / 4 papers shown

Selecting User Histories to Generate LLM Users for Cold-Start Item Recommendation

116

27 Nov 2025

R-Block: Regularized Block of Dropout for convolutional networks

Liqi Wang

Qiyang Hu

118

27 Jul 2023

Position: Tensor Networks are a Valuable Asset for Green AIInternational Conference on Machine Learning (ICML), 2022

312

25 May 2022

S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization

363

1,023

18 Aug 2020