111 citations · 149 across the 14 of their papers we have counts for
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cs.AI2018★ 14 cited
Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning
Jun Feng, Heng Li, Minlie Huang +4
Ranking is a fundamental and widely studied problem in scenarios such as search, advertising, and recommendation. However, joint optimization for multi-scenario ranking, which aims…
stat.ML2018★ 24 cited
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks
Yabo Ni, Dan Ou, Shichen Liu +4
Tasks such as search and recommendation have become increas- ingly important for E-commerce to deal with the information over- load problem. To meet the diverse needs of di erent u…