Memory-Efficient Deep Recommender Systems using Approximate Rotary Compositional Embedding
Author:
Affiliation:
1. Villanova University, Villanova, PA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657953
Reference17 articles.
1. Wide & Deep Learning for Recommender Systems
2. Random offset block embedding (robe) for compressed embedding tables in deep learning recommendation systems;Desai Aditya;Proceedings of Machine Learning and Systems,2022
3. Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems
4. Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He. Deepfm: a factorization-machine based neural network for ctr prediction. arXiv preprint arXiv:1703.04247, 2017.
5. Learning to Embed Categorical Features without Embedding Tables for Recommendation
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