6 papers
Multivariate Time Series Data Imputation via Distributionally Robust Regularization
Che-Yi Liao, Zheng Dong, Gian-Gabriel Garcia +1
Multivariate time series imputation is often compromised by mismatch between the observed and true data distributions, a bias induced by the combined effects of time-series non-sta…
GreenTEA: Gradient Descent with Topic-modeling and Evolutionary Auto-prompting
Zheng Dong, Luming Shang, Gabriela Olinto
High-quality prompts are crucial for Large Language Models (LLMs) to achieve exceptional performance. However, manually crafting effective prompts is labor-intensive and demands si…
Deep spatio-temporal point processes: Advances and new directions
Xiuyuan Cheng, Zheng Dong, Yao Xie
Spatio-temporal point processes (STPPs) model discrete events distributed in time and space, with important applications in areas such as criminology, seismology, epidemiology, and…
Spatio-Temporal-Network Point Processes for Modeling Crime Events with Landmarks
Zheng Dong, Jorge Mateu, Yao Xie
Self-exciting point processes are widely used to model the contagious effects of crime events living within continuous geographic space, using their occurrence time and locations.…
Atlanta Gun Violence Modeling via Nonstationary Spatio-temporal Point Processes
Zheng Dong, Yao Xie
Analysis of gun violence in the United States has utilized various models based on spatiotemporal point processes. Previous studies have identified a contagion effect in gun violen…
Debiased Model-based Interactive Recommendation
Zijian Li, Ruichu Cai, Haiqin Huang +4
Existing model-based interactive recommendation systems are trained by querying a world model to capture the user preference, but learning the world model from historical logged da…