A Sample‐Efficient Actor‐Critic Algorithm for Recommendation Diversification
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DOI: 10.1049/cje.2019.10.004
Abstract: Diversifying recommendation results gains benefits from satisfying user's existing interests as well as exploring novel information needs. Recently proposed Monte-Carlo based reinforcement learning method suffers from sample inefficiency, large variance, and even failing to perform… read more here.
Keywords: algorithm recommendation; recommendation; actor; actor critic ... See more keywords
Algorithm Recommendation and Performance Prediction Using Meta-Learning
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DOI: 10.1142/s0129065723500119
Abstract: In the last years, the number of machine learning algorithms and their parameters has increased significantly. On the one hand, this increases the chances of finding better models. On the other hand, it increases the… read more here.
Keywords: meta learning; algorithm recommendation; machine learning; model ... See more keywords