PriSHAP: Prior-guided Shapley Value Explanations for Correlated Features.

@inproceedings{jiang-2023-prishap, author = {Guanyu Jiang and Fuzhen Zhuang and Bowen Song and Tianyi Zhang and Deqing Wang}, editor = {Ingo Frommholz and Frank Hopfgartner and Mark Lee and Michael P. Oakes and Mounia Lalmas-Roelleke and Min Zhang and Rodrygo L. T. Santos}, title = {{PriSHAP: Prior-guided Shapley Value Explanations for Correlated Features}}, booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}}, pages = {955--964}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3583780.3615013}, doi = {https://doi.org/10.1145/3583780.3615013} }