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Found 3 papers, 1 papers with code
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Model
High-concurrency asynchronous training upon parameter server (PS) architecture and high-performance synchronous training upon all-reduce (AR) architecture are the most commonly deployed distributed training modes for recommendation models.
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems
However, we observe that GPU devices in training recommender systems are underutilized, and they cannot attain an expected throughput improvement as what it has achieved in CV and NLP areas.
Image Matters: Visually modeling user behaviors using Advanced Model Server
So we propose to model user preference jointly with user behavior ID features and behavior images.
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