Embedding Samples Dispatching for Recommendation Model Training in Edge Environments
Published:Dec 25, 2025 10:23
•1 min read
•ArXiv
Analysis
This article likely discusses a method for efficiently training recommendation models in edge computing environments. The focus is on how to distribute embedding samples, which are crucial for these models, to edge devices for training. The use of edge environments suggests a focus on low-latency and privacy-preserving recommendations.
Key Takeaways
- •Focus on training recommendation models in edge environments.
- •Addresses the efficient distribution of embedding samples.
- •Implies a focus on low-latency and privacy-preserving recommendations.
Reference
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