89 citations · 226 across the 13 of their papers we have counts for
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cs.LG2020★ 1 cited
Temporal Network Representation Learning via Historical Neighborhoods Aggregation
Shixun Huang, Zhifeng Bao, Guoliang Li +2
Network embedding is an effective method to learn low-dimensional representations of nodes, which can be applied to various real-life applications such as visualization, node class…
cs.LG2019★ 3 cited
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms
Caihua Shan, Nikos Mamoulis, Reynold Cheng +3
In this paper, we propose a Deep Reinforcement Learning (RL) framework for task arrangement, which is a critical problem for the success of crowdsourcing platforms. Previous works…