463 citations · 1.1k across the 22 of their papers we have counts for
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Beyond Double Ascent via Recurrent Neural Tangent Kernel in Sequential Recommendation
Ruihong Qiu, Zi Huang, Hongzhi Yin
Overfitting has long been considered a common issue to large neural network models in sequential recommendation. In our study, an interesting phenomenon is observed that overfittin…
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
Ruihong Qiu, Zi Huang, Hongzhi Yin +1
Recent advancements of sequential deep learning models such as Transformer and BERT have significantly facilitated the sequential recommendation. However, according to our study, t…
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation
Ruihong Qiu, Zi Huang, Hongzhi Yin
The sequential recommendation aims to recommend items, such as products, songs and places, to users based on the sequential patterns of their historical records. Most existing sequ…
CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation
Ruihong Qiu, Sen Wang, Zhi Chen +2
Visually-aware recommendation on E-commerce platforms aims to leverage visual information of items to predict a user's preference. It is commonly observed that user's attention to…
Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks
Ruihong Qiu, Zi Huang, Jingjing Li +1
Different from the traditional recommender system, the session-based recommender system introduces the concept of the session, i.e., a sequence of interactions between a user and m…
Exploiting Positional Information for Session-based Recommendation
Ruihong Qiu, Zi Huang, Tong Chen +1
For present e-commerce platforms, session-based recommender systems are developed to predict users' preference for next-item recommendation. Although a session can usually reflect…
GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation
Ruihong Qiu, Hongzhi Yin, Zi Huang +1
Streaming session-based recommendation (SSR) is a challenging task that requires the recommender system to do the session-based recommendation (SR) in the streaming scenario. In th…
Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks
Ruihong Qiu, Jingjing Li, Zi Huang +1
Predicting a user's preference in a short anonymous interaction session instead of long-term history is a challenging problem in the real-life session-based recommendation, e.g., e…