{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:28:47Z","timestamp":1740101327608,"version":"3.37.3"},"reference-count":44,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100015539","name":"Australian Government","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100015539","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,13]]},"DOI":"10.1109\/dsaa54385.2022.10032417","type":"proceedings-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T18:54:03Z","timestamp":1675882443000},"page":"1-9","source":"Crossref","is-referenced-by-count":1,"title":["Evidence Based Pipeline for Explaining Artificial Intelligence Algorithms with Interactions"],"prefix":"10.1109","author":[{"given":"Ambreen","family":"Hanif","sequence":"first","affiliation":[{"name":"Macquarie University,School of Computer Science,Sydney,Australia"}]},{"given":"Amin","family":"Beheshti","sequence":"additional","affiliation":[{"name":"Macquarie University,School of Computer Science,Sydney,Australia"}]},{"given":"Boualem","family":"Benatallah","sequence":"additional","affiliation":[{"name":"Dublin City University,School of Computing, ADAPT,Dublin,Ireland"}]},{"given":"Xuyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Macquarie University,School of Computer Science,Sydney,Australia"}]},{"given":"Steven","family":"Wood","sequence":"additional","affiliation":[{"name":"Prospa Advance Pty. Ltd,Sydney,Australia"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature16961"},{"article-title":"Dota 2 with Large Scale Deep Reinforcement Learning","year":"2019","author":"Berner","key":"ref2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1126\/science.aay2400"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.5853\/jos.2017.02054"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2017.06.016"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0048-x"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S1071-5819(03)00038-7"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-019-1426-2"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aay7120"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.4324\/9781003004790-1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1093\/idpl\/ipx005"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v38i3.2741"},{"article-title":"Interpretable Machine Learning","year":"2021","author":"Molnar","key":"ref14"},{"article-title":"Explainable Artificial Intelligence Approaches: A Survey","year":"2021","author":"Islam","key":"ref15"},{"article-title":"Towards A Rigorous Science of Interpretable Machine Learning","year":"2017","author":"Doshi-Velez","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2983930"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.907095"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12377"},{"key":"ref22","first-page":"1135","article-title":"Why should i trust you?","volume-title":"Explaining the predictions of any classifier. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Ribeiro"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3321\/j.issn:0529-6579.2007.z1.029"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"article-title":"SmoothGrad: removing noise by adding noise","year":"2017","author":"Smilkov","key":"ref25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref27","first-page":"5109","article-title":"Axiomatic Attribution for Deep Networks","volume-title":"34th International Conference on Machine Learning, ICML 2017","volume":"7","author":"Sundararajan"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"volume-title":"Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges \u2014 IOS Press","year":"2020","author":"Tiddi","key":"ref29"},{"key":"ref30","article-title":"Towards Automatic Concept-based Explanations","volume":"32","author":"Ghorbani","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref31","first-page":"4186","article-title":"Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)","volume-title":"35th International Conference on Machine Learning, ICML 2018","volume":"6","author":"Kim"},{"key":"ref32","article-title":"Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning","volume-title":"CEUR Workshop Proceedings","volume":"2600","author":"Kursuncu"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00516"},{"article-title":"An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks","year":"2020","author":"Schlegel","key":"ref34"},{"key":"ref35","first-page":"210","article-title":"Shapley Value","author":"Hart","year":"1989","journal-title":"Game Theory"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3236009"},{"author":"Kijko","key":"ref37","article-title":"The Best Tools for Machine Learning Model Visualization - neptune.ai"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2934619"},{"article-title":"Playing with AI Fairness","year":"2021","author":"Weinberger","key":"ref39"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3306618.3314293"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.07.014"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/DISA.2018.8490530"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/MCG.2020.3017064"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60117-1_33"}],"event":{"name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","start":{"date-parts":[[2022,10,13]]},"location":"Shenzhen, China","end":{"date-parts":[[2022,10,16]]}},"container-title":["2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10032305\/10032324\/10032417.pdf?arnumber=10032417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T10:56:58Z","timestamp":1707821818000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10032417\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,13]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/dsaa54385.2022.10032417","relation":{},"subject":[],"published":{"date-parts":[[2022,10,13]]}}}