Shapley Based Residual Decomposition for Instance Analysis
| dc.contributor.author | Liu, Tommy | en |
| dc.contributor.author | Barnard, Amanda | en |
| dc.date.accessioned | 2025-06-24T01:36:49Z | |
| dc.date.available | 2025-06-24T01:36:49Z | |
| dc.date.issued | 2023 | en |
| dc.description.abstract | In this paper, we introduce the idea of decomposing the residuals of regression with respect to the data instances instead of features. This allows us to determine the effects of each individual instance on the model and each other, and in doing so makes for a model-agnostic method of identifying instances of interest. In doing so, we can also determine the appropriateness of the model and data in the wider context of a given study. The paper focuses on the possible applications that such a framework brings to the relatively unexplored field of instance analysis in the context of Explainable AI tasks. | en |
| dc.description.sponsorship | This research/project was undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government, along with support by an Australian Government Research Training Program (RTP) Scholarship. | en |
| dc.description.status | Peer-reviewed | en |
| dc.format.extent | 22 | en |
| dc.identifier.other | ORCID:/0000-0002-4784-2382/work/161120551 | en |
| dc.identifier.scopus | 85174410080 | en |
| dc.identifier.uri | http://www.scopus.com/inward/record.url?scp=85174410080&partnerID=8YFLogxK | en |
| dc.identifier.uri | https://hdl.handle.net/1885/733764611 | |
| dc.language.iso | en | en |
| dc.relation.ispartofseries | 40th International Conference on Machine Learning, ICML 2023 | en |
| dc.rights | Publisher Copyright: © 2023 Proceedings of Machine Learning Research. All rights reserved. | en |
| dc.source | Proceedings of Machine Learning Research | en |
| dc.title | Shapley Based Residual Decomposition for Instance Analysis | en |
| dc.type | Conference paper | en |
| dspace.entity.type | Publication | en |
| local.bibliographicCitation.lastpage | 21936 | en |
| local.bibliographicCitation.startpage | 21915 | en |
| local.contributor.affiliation | Liu, Tommy; School of Computing, ANU College of Systems and Society, The Australian National University | en |
| local.contributor.affiliation | Barnard, Amanda; School of Computing, ANU College of Systems and Society, The Australian National University | en |
| local.identifier.ariespublication | a383154xPUB44236 | en |
| local.identifier.citationvolume | 202 | en |
| local.identifier.pure | 772f03ca-6db7-4a1e-8d22-6f7b86b2077e | en |
| local.identifier.url | https://www.scopus.com/pages/publications/85174410080 | en |
| local.type.status | Published | en |