Qiao Liu

Generalized Graph Embedding Models

2018

Many types of relations in physical, biological, social and information systems can be modeled as homogeneous or heterogeneous concept graphs. Hence, learning from and with graph embeddings has drawn a great deal of research interest …

CausalEGM: a general causal inference framework by encoding generative modeling

2022 · arXiv (Cornell University)

Although understanding and characterizing causal effects have become essential in observational studies, it is challenging when the confounders are high-dimensional. In this article, we develop a general framework $\textit{CausalEGM}$ for estimating causal effects by encoding …

Exploiting Inter-Session Information with Frequency-enhanced Dual-Path Networks for Sequential Recommendation

2026 · Proceedings of the AAAI Conference on Artificial Intelligence

Sequential recommendation (SR) aims to predict a user's next item preference by modeling historical interaction sequences. Recent advances often integrate frequency-domain modules to compensate for self-attention's low-pass nature by restoring the high-frequency signals critical for …

STAMP

2018

Predicting users' actions based on anonymous sessions is a challenging problem in web-based behavioral modeling research, mainly due to the uncertainty of user behavior and the limited information. Recent advances in recurrent neural networks have …