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Found 4 papers, 2 papers with code
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Specifically, in order to ensure both the training efficiency and the training accuracy, we design a novel hybrid training algorithm, where the embedding layer and the dense neural network are handled by different synchronization mechanisms; then we build a system called Persia (short for parallel recommendation training system with hybrid acceleration) to support this hybrid training algorithm.
POSO: Personalized Cold Start Modules for Large-scale Recommender Systems
Moreover, POSO can be further generalized to regular users, inactive users and returning users (+2%-3% on Watch Time), as well as item cold start (+3. 8% on Watch Time).
Using Query Expansion in Manifold Ranking for Query-Oriented Multi-Document Summarization
It not only makes use of the relationships among the sentences, but also the relationships between the given query and the sentences.
Joint Lifelong Topic Model and Manifold Ranking for Document Summarization
The JTMMR model can improve the effect of the manifold ranking method by using the better semantic feature.
