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Learning to Embed Categorical Features without Embedding Tables for Recommendation

Learning to Embed Categorical Features without Embedding Tables for Recommendation

Wang-Cheng Kang
D. Cheng
Tiansheng Yao
Xinyang Yi
Ting-Li Chen
Lichan Hong
Ed H. Chi
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Papers citing "Learning to Embed Categorical Features without Embedding Tables for Recommendation"

5 / 5 papers shown
Title
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
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
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
DreamShard: Generalizable Embedding Table Placement for Recommender Systems
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
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
Learnable Embedding Sizes for Recommender Systems
Siyi Liu
Chen Gao
Yihong Chen
Depeng Jin
Yong Li
52
70
0
19 Jan 2021