9 papers
Priority-Aware Shapley Value
Kiljae Lee, Ziqi Liu, Weijing Tang +1
Shapley values are widely used for model-agnostic data valuation and feature attribution, yet they implicitly assume contributors are interchangeable. This can be problematic when…
Inference for Balance in Dynamic Signed Networks
Ergan Shang, Yuan Zhang, Weijing Tang
Signed networks consist of both positive and negative relations, and structural balance theory provides an important conceptural framework for understanding their global tension st…
Generalized Priority-Aware Shapley Value
Kiljae Lee, Ziqi Liu, Weijing Tang +1
Shapley value and its priority-aware extensions are widely used for valuation in machine learning, but existing methods require pairwise priority to be binary and acyclic, a restri…
First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint
Ziqi Liu, Kiljae Lee, Yuan Zhang +1
Probabilistic values, including Shapley values and semivalues, provide a model-agnostic framework to attribute the behavior of a black-box model to data points or features, with a…
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…
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…