Enhancing Top-N Item Recommendations by Peer Collaboration

  title={Enhancing Top-N Item Recommendations by Peer Collaboration},
  author={Yang Sun and Fajie Yuan and Min Yang and Alexandros Karatzoglou and Shen Li and Xiaoyan Zhao},
  journal={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  • Yang Sun, Fajie Yuan, Xiaoyan Zhao
  • Published 31 October 2021
  • Computer Science
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
Deep neural networks (DNN) based recommender models often require numerous parameters to achieve remarkable performance. However, this inevitably brings redundant neurons, a phenomenon referred to as over-parameterization. In this paper, we plan to exploit such redundancy phenomena for recommender systems (RS), and propose a top-N item recommendation framework called PCRec that leverages collaborative training of two recommender models of the same network structure, termed peer collaboration… 

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