21 citations · 26 across the 2 of their papers we have counts for
2 papers
cs.IR2021★ 5 cited
AutoLoss: Automated Loss Function Search in Recommendations
Xiangyu Zhao, Haochen Liu, Wenqi Fan +3
Designing an effective loss function plays a crucial role in training deep recommender systems. Most existing works often leverage a predefined and fixed loss function that could l…
cs.IR2020★ 21 cited
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
Xiangyu Zhao, Chong Wang, Ming Chen +3
Deep learning based recommender systems (DLRSs) often have embedding layers, which are utilized to lessen the dimensionality of categorical variables (e.g. user/item identifiers) a…