1 citations · 2 across the 5 of their papers we have counts for
5 papers
Rethinking Data Value: Asymmetric Data Shapley for Structure-Aware Valuation in Data Markets and Machine Learning Pipelines
Xi Zheng, Yinghui Huang, Xiangyu Chang +2
Rigorous valuation of individual data sources is critical for fair compensation in data markets, informed data acquisition, and transparent development of ML/AI models. Classical D…
Towards Data Valuation via Asymmetric Data Shapley
Xi Zheng, Xiangyu Chang, Ruoxi Jia +1
As data emerges as a vital driver of technological and economic advancements, a key challenge is accurately quantifying its value in algorithmic decision-making. The Shapley value,…
Uncertainty Quantification of Data Shapley via Statistical Inference
Mengmeng Wu, Zhihong Liu, Xiang Li +2
As data plays an increasingly pivotal role in decision-making, the emergence of data markets underscores the growing importance of data valuation. Within the machine learning lands…
2D-Shapley: A Framework for Fragmented Data Valuation
Zhihong Liu, Hoang Anh Just, Xiangyu Chang +2
Data valuation -- quantifying the contribution of individual data sources to certain predictive behaviors of a model -- is of great importance to enhancing the transparency of mach…
Variance reduced Shapley value estimation for trustworthy data valuation
Mengmeng Wu, Ruoxi Jia, Changle Lin +2
Data valuation, especially quantifying data value in algorithmic prediction and decision-making, is a fundamental problem in data trading scenarios. The most widely used method is…