WebSHAP: Towards Explaining Any Machine Learning Models Anywhere.

Zijie J. Wang|Duen Horng Chau


Anthology ID:DBLP:conf/www/WangC23a
Volume:Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023
Year:2023
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:262-266
URL:https://doi.org/10.1145/3543873.3587362
DOI:https://doi.org/10.1145/3543873.3587362
DBLP:conf/www/WangC23a
BibTeX:
@inproceedings{wang-2023-webshap, author = {Zijie J. Wang and Duen Horng Chau}, editor = {Ying Ding and Jie Tang and Juan F. Sequeda and Lora Aroyo and Carlos Castillo and Geert-Jan Houben}, title = {{WebSHAP: Towards Explaining Any Machine Learning Models Anywhere}}, booktitle = {{Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}}, pages = {262--266}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3543873.3587362}, doi = {https://doi.org/10.1145/3543873.3587362} }