5.7k citations · 8.9k across the 11 of their papers we have counts for
4 papers · 1 filter
Deep Retrieval: Learning A Retrievable Structure for Large-Scale Recommendations
Weihao Gao, Xiangjun Fan, Chong Wang +7
One of the core problems in large-scale recommendations is to retrieve top relevant candidates accurately and efficiently, preferably in sub-linear time. Previous approaches are mo…
Jointly Learning to Recommend and Advertise
Xiangyu Zhao, Xudong Zheng, Xiwang Yang +2
Online recommendation and advertising are two major income channels for online recommendation platforms (e.g. e-commerce and news feed site). However, most platforms optimize recom…
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
Xiangyu Zhao, Chong Wang, Ming Chen +3
Deep learning based recommender systems (DLRSs) often have embedding layers, which are utilized to lessen the dimensionality of categorical variables (e.g. user/item identifiers) a…
Learning to Structure Long-term Dependence for Sequential Recommendation
Renqin Cai, Qinglei Wang, Chong Wang +1
Sequential recommendation recommends items based on sequences of users' historical actions. The key challenge in it is how to effectively model the influence from distant actions t…