Diffusion models have demonstrated competitive performance in missing data imputation
(MDI) task. However, directly applying diffusion models to MDI produces suboptimal …

Post-click conversion rate (CVR) estimation is a fundamental task in develo** effective
recommender systems, yet it faces challenges from data sparsity and sample selection bias …

Accurate imputation of missing data is pivotal in real-world industrial applications.
Traditional direct imputers, which utilize basic statistics to replace missing elements, offer a …

Recommendation systems (RS) have become integral to numerous digital platforms and
applications, ranging from e-commerce to content streaming field. A critical problem in RS is …

Multimedia recommendation systems aim to accurately predict user preferences from
multimodal data. However, existing methods may learn a recommendation model from …

Recommender systems (RS) help to capture users' personalized interests and are
increasingly important across social media, e-commerce, and various online applications …

Heterogeneous treatment effect (HTE) estimation from observational data poses significant
challenges due to treatment selection bias. Existing methods address this bias by …

Recommendation systems (RS) has become integral to numerous applications, ranging
from e-commerce to content streaming. A critical problem in RS is that the ratings are …

In the information era, recommendation systems play a crucial role in mitigating information
overload by predicting user preferences based on historical interactions. However …

Recommender systems (RS) are increasingly important in social media, entertainment, and
e-commerce in the information explosion era. However, the collected data contains many …