32 citations · 33 across the 8 of their papers we have counts for
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cs.LG2023
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models
Hailin Zhang, Zirui Liu, Boxuan Chen +4
Recently, the growing memory demands of embedding tables in Deep Learning Recommendation Models (DLRMs) pose great challenges for model training and deployment. Existing embedding…
cs.LG2023
Experimental Analysis of Large-scale Learnable Vector Storage Compression
Hailin Zhang, Penghao Zhao, Xupeng Miao +4
Learnable embedding vector is one of the most important applications in machine learning, and is widely used in various database-related domains. However, the high dimensionality o…
cs.NI2023★ 32 cited
ChameleMon: Shifting Measurement Attention as Network State Changes
Kaicheng Yang, Yuhan Wu, Ruijie Miao +8
Flow-level network measurement is critical to many network applications. Among various measurement tasks, packet loss detection and heavy-hitter detection are two most important me…