One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation.

@inproceedings{li-2023-one, author = {Chenglin Li and Yuanzhen Xie and Chenyun Yu and Bo Hu and Zang Li and Guoqiang Shu and Xiaohu Qie and Di Niu}, editor = {Tat-Seng Chua and Hady Wirawan Lauw and Luo Si and Evimaria Terzi and Panayiotis Tsaparas}, title = {{One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation}}, booktitle = {{Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, WSDM 2023, Singapore, 27 February 2023 - 3 March 2023}}, pages = {366--374}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3539597.3570379}, doi = {https://doi.org/10.1145/3539597.3570379} }