DIWIFT: Discovering Instance-wise Influential Features for Tabular Data.

Dugang Liu|Pengxiang Cheng|Hong Zhu|Xing Tang|Yanyu Chen|Xiaoting Wang|Weike Pan|Zhong Ming|Xiuqiang He


Anthology ID:DBLP:conf/www/Liu0Z0CWP0023
Volume: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:1673-1682
URL:https://doi.org/10.1145/3543507.3583382
DOI:https://doi.org/10.1145/3543507.3583382
DBLP:conf/www/Liu0Z0CWP0023
BibTeX:
@inproceedings{liu-2023-diwift, author = {Dugang Liu and Pengxiang Cheng and Hong Zhu and Xing Tang and Yanyu Chen and Xiaoting Wang and Weike Pan and Zhong Ming and Xiuqiang He}, editor = {Ying Ding and Jie Tang and Juan F. Sequeda and Lora Aroyo and Carlos Castillo and Geert-Jan Houben}, title = {{DIWIFT: Discovering Instance-wise Influential Features for Tabular Data}}, booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}}, pages = {1673--1682}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3543507.3583382}, doi = {https://doi.org/10.1145/3543507.3583382} }