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Found 2 papers, 2 papers with code
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking
We validate the performance of StackRec by instantiating it with four state-of-the-art SR models in three practical scenarios with real-world datasets.
One Person, One Model, One World: Learning Continual User Representation without Forgetting
In this paper, we delve on research to continually learn user representations task by task, whereby new tasks are learned while using partial parameters from old ones.
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