Learning to Embed Categorical Features without Embedding Tables for Recommendation

21 October 2020

Papers citing "Learning to Embed Categorical Features without Embedding Tables for Recommendation"

6 / 6 papers shown

Title
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems Hung Vinh Tran Tong Chen Quoc Viet Hung Nguyen Zi-Rui Huang Lizhen Cui Hongzhi Yin 36 1 0 25 Jun 2024
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation Gopu Krishna Jha Anthony Thomas Nilesh Jain Sameh Gobriel Tajana Rosing Ravi Iyer 32 2 0 12 May 2023
Clustering the Sketch: A Novel Approach to Embedding Table Compression Henry Ling-Hei Tsang Thomas Dybdahl Ahle 14 1 0 12 Oct 2022
DreamShard: Generalizable Embedding Table Placement for Recommender Systems Daochen Zha Louis Feng Qiaoyu Tan Zirui Liu Kwei-Herng Lai Bhargav Bhushanam Yuandong Tian A. Kejariwal Xia Hu LMTD OffRL 8 28 0 05 Oct 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 20 30 0 30 May 2022
Learnable Embedding Sizes for Recommender Systems Siyi Liu Chen Gao Yihong Chen Depeng Jin Yong Li 52 70 0 19 Jan 2021