7 citations · 14 across the 10 of their papers we have counts for
10 papers
Out-of-Distribution Generalization in Time Series: A Survey
Xin Wu, Fei Teng, Xingwang Li +3
Time series frequently manifest distribution shifts, diverse latent features, and non-stationary learning dynamics, particularly in open and evolving environments. These characteri…
Variational Bayesian Personalized Ranking
Bin Liu, Xiaohong Liu, Qin Luo +7
Pairwise learning underpins implicit collaborative filtering, yet its effectiveness is often hindered by sparse supervision, noisy interactions, and popularity-driven exposure bias…
Beyond Fixed Variables: Expanding-variate Time Series Forecasting via Flat Scheme and Spatio-temporal Focal Learning
Minbo Ma, Kai Tang, Huan Li +3
Multivariate Time Series Forecasting (MTSF) has long been a key research focus. Traditionally, these studies assume a fixed number of variables, but in real-world applications, Cyb…
A Survey of Route Recommendations: Methods, Applications, and Opportunities
Shiming Zhang, Zhipeng Luo, Li Yang +2
Nowadays, with advanced information technologies deployed citywide, large data volumes and powerful computational resources are intelligentizing modern city development. As an impo…
Continual Learning for Smart City: A Survey
Li Yang, Zhipeng Luo, Shiming Zhang +2
With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continua…
Self-supervised Contrastive Learning for Implicit Collaborative Filtering
Shipeng Song, Bin Liu, Fei Teng +1
Contrastive learning-based recommendation algorithms have significantly advanced the field of self-supervised recommendation, particularly with BPR as a representative ranking pred…
Learning Contrastive Feature Representations for Facial Action Unit Detection
Ziqiao Shang, Bin Liu, Fengmao Lv +3
For the Facial Action Unit (AU) detection task, accurately capturing the subtle facial differences between distinct AUs is essential for reliable detection. Additionally, AU detect…
Learning Time-aware Graph Structures for Spatially Correlated Time Series Forecasting
Minbo Ma, Jilin Hu, Christian S. Jensen +4
Spatio-temporal forecasting of future values of spatially correlated time series is important across many cyber-physical systems (CPS). Recent studies offer evidence that the use o…
A Missing Value Filling Model Based on Feature Fusion Enhanced Autoencoder
Xinyao Liu, Shengdong Du, Tianrui Li +2
With the advent of the big data era, the data quality problem is becoming more critical. Among many factors, data with missing values is one primary issue, and thus developing effe…
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting
Minbo Ma, Peng Xie, Fei Teng +4
Weather Forecasting is an attractive challengeable task due to its influence on human life and complexity in atmospheric motion. Supported by massive historical observed time serie…