3 papers
stat.ME2026
Representation Learning with Blockwise Missingness and Signal Heterogeneity
Ziqi Liu, Ye Tian, Weijing Tang
Unified representation learning for multi-source data integration faces two important challenges: blockwise missingness and blockwise signal heterogeneity. The former arises from s…
cs.LG2025
Measuring Fine-Grained Relatedness in Multitask Learning via Data Attribution
Yiwen Tu, Ziqi Liu, Jiaqi W. Ma +1
Measuring task relatedness and mitigating negative transfer remain a critical open challenge in Multitask Learning (MTL). This work extends data attribution -- which quantifies the…
cs.LG2025
Faithful Group Shapley Value
Kiljae Lee, Ziqi Liu, Weijing Tang +1
Data Shapley is an important tool for data valuation, which quantifies the contribution of individual data points to machine learning models. In practice, group-level data valuatio…