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Found 3 papers, 1 papers with code
Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations
User states in different channels are updated by an \emph{erase-and-add} paradigm with interest- and instance-level attention.
Multi-Channel Sequential Behavior Networks for User Modeling in Online Advertising
Multiple content providers rely on native advertisement for revenue by placing ads within the organic content of their pages.
A Mixtures-of-Experts Framework for Multi-Label Classification
We develop a novel probabilistic approach for multi-label classification that is based on the mixtures-of-experts architecture combined with recently introduced conditional tree-structured Bayesian networks.
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