16 citations · 32 across the 11 of their papers we have counts for
11 papers
Liquid Gated Attention
Yiheng Jiang, Yuanbo Xu, Yongjian Yang
Real-world time series often exhibit irregular sampling and extended temporal horizons, requiring models to capture continuous-time dynamics across arbitrary intervals without proh…
Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach
Jialei Chen, Yuanbo Xu, Yiheng Jiang
In this paper, we focus on the often-overlooked issue of embedding collapse in existing diffusion-based sequential recommendation models and propose ADRec, an innovative framework…
DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops
Hangtong Xu, Yuanbo Xu, Yongjian Yang +2
Recommendation models trained on the user feedback collected from deployed recommendation systems are commonly biased. User feedback is considerably affected by the exposure mechan…
Causal Structure Representation Learning of Confounders in Latent Space for Recommendation
Hangtong Xu, Yuanbo Xu, Chaozhuo Li +1
Inferring user preferences from the historical feedback of users is a valuable problem in recommender systems. Conventional approaches often rely on the assumption that user prefer…
Separating and Learning Latent Confounders to Enhancing User Preferences Modeling
Hangtong Xu, Yuanbo Xu, Yongjian Yang
Recommender models aim to capture user preferences from historical feedback and then predict user-specific feedback on candidate items. However, the presence of various unmeasured…
Deep Generative Imputation Model for Missing Not At Random Data
Jialei Chen, Yuanbo Xu, Pengyang Wang +1
Data analysis usually suffers from the Missing Not At Random (MNAR) problem, where the cause of the value missing is not fully observed. Compared to the naive Missing Completely At…
TriMLP: Revenge of a MLP-like Architecture in Sequential Recommendation
Yiheng Jiang, Yuanbo Xu, Yongjian Yang +3
In this paper, we present a MLP-like architecture for sequential recommendation, namely TriMLP, with a novel Triangular Mixer for cross-token communications. In designing Triangula…
Detect Professional Malicious User with Metric Learning in Recommender Systems
Yuanbo Xu, Yongjian Yang, En Wang +2
In e-commerce, online retailers are usually suffering from professional malicious users (PMUs), who utilize negative reviews and low ratings to their consumed products on purpose t…
A Unified Collaborative Representation Learning for Neural-Network based Recommender Systems
Yuanbo Xu, En Wang, Yongjian Yang +1
Most NN-RSs focus on accuracy by building representations from the direct user-item interactions (e.g., user-item rating matrix), while ignoring the underlying relatedness between…
Symmetric Transformer-based Network for Unsupervised Image Registration
Mingrui Ma, Lei Song, Yuanbo Xu +1
Medical image registration is a fundamental and critical task in medical image analysis. With the rapid development of deep learning, convolutional neural networks (CNN) have domin…
Generating Self-Serendipity Preference in Recommender Systems for Addressing Cold Start Problems
Yuanbo Xu, Yongjian Yang, En Wang
Classical accuracy-oriented Recommender Systems (RSs) typically face the cold-start problem and the filter-bubble problem when users suffer the familiar, repeated, and even predict…