4 papers
SP-GCRL: Influence Maximization on Incomplete Social Graphs
Haohua Niu, Yuxuan Yang, Lingfeng Zhang +4
Influence maximization (IM) in real platforms is challenged by incomplete, noisy social graphs and non-stationary diffusion dynamics. We propose SP-GCRL, a social-propagation-aware…
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
Xiaorui Wang, Fanda Fan, Chenxi Wang +9
Recent progress in time-series forecasting has led to rapidly increasing architectural complexity, yet many reported State-of-the-Art gains are statistically fragile or misattribut…
Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
Yuxuan Yang, Dalin Zhang, Yuxuan Liang +3
Time Series Forecasting (TSF) is a crucial task in various domains, yet existing TSF models rely heavily on high-quality data and insufficiently exploit all available data. This pa…
Ensembling Membership Inference Attacks Against Tabular Generative Models
Joshua Ward, Yuxuan Yang, Chi-Hua Wang +1
Membership Inference Attacks (MIAs) have emerged as a principled framework for auditing the privacy of synthetic data generated by tabular generative models, where many diverse met…