CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation

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Other Links: arxiv.org

Abstract:

Sampling strategies have been widely applied in many recommendation systems to accelerate model learning from implicit feedback data. A typical strategy is to draw negative instances with uniform distribution, which however will severely affect model's convergency, stability, and even recommendation accuracy. A promising solution for th...More

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