152 citations · 256 across the 30 of their papers we have counts for
4 papers · 1 filter
Efficient Diversity-Driven Ensemble for Deep Neural Networks
Wentao Zhang, Jiawei Jiang, Yingxia Shao +1
The ensemble of deep neural networks has been shown, both theoretically and empirically, to improve generalization accuracy on the unseen test set. However, the high training cost…
Self-Supervised Graph Co-Training for Session-based Recommendation
Xin Xia, Hongzhi Yin, Junliang Yu +2
Session-based recommendation targets next-item prediction by exploiting user behaviors within a short time period. Compared with other recommendation paradigms, session-based recom…
Matching-oriented Product Quantization For Ad-hoc Retrieval
Shitao Xiao, Zheng Liu, Yingxia Shao +2
Product quantization (PQ) is a widely used technique for ad-hoc retrieval. Recent studies propose supervised PQ, where the embedding and quantization models can be jointly trained…
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop
Shitao Xiao, Zheng Liu, Yingxia Shao +2
News recommendation calls for deep insights of news articles' underlying semantics. Therefore, pretrained language models (PLMs), like BERT and RoBERTa, may substantially contribut…