{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T10:23:21Z","timestamp":1768213401596,"version":"3.49.0"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031703584","type":"print"},{"value":"9783031703591","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-70359-1_26","type":"book-chapter","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T04:02:43Z","timestamp":1724904163000},"page":"437-453","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Model Agnostic Explanations via\u00a0Constraint Programming"],"prefix":"10.1007","author":[{"given":"Frederic","family":"Koriche","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean-Marie","family":"Lagniez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Mengel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chi","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"26_CR1","unstructured":"Arenas, M., Barcel\u00f3, P., Orth, M.A.R., Subercaseaux, B.: On computing probabilistic explanations for decision trees. In: Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS) (2022)"},{"key":"26_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2022.102088","volume":"142","author":"G Audemard","year":"2022","unstructured":"Audemard, G., Bellart, S., Bounia, L., Koriche, F., Lagniez, J., Marquis, P.: On the explanatory power of Boolean decision trees. Data Knowl. Eng. 142, 102088 (2022)","journal-title":"Data Knowl. Eng."},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Audemard, G., Bellart, S., Bounia, L., Koriche, F., Lagniez, J., Marquis, P.: Trading complexity for sparsity in random forest explanations. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence, pp. 5461\u20135469 (2022)","DOI":"10.1609\/aaai.v36i5.20484"},{"key":"26_CR4","unstructured":"Blanc, G., Lange, J., Tan, L.: Provably efficient, succinct, and precise explanations. In: Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems (NeurIPS), pp. 6129\u20136141 (2021)"},{"key":"26_CR5","unstructured":"Bounia, L., Koriche, F.: Approximating probabilistic explanations via supermodular minimization. In: Proceedings of the 39th International Conference on Uncertainty in Artificial Intelligence (UAI). PMLR, vol.\u00a0216, pp. 216\u2013225 (2023)"},{"key":"26_CR6","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1613\/jair.1.12228","volume":"70","author":"N Burkart","year":"2021","unstructured":"Burkart, N., Huber, M.F.: A survey on the explainability of supervised machine learning. J. Artif. Intell. Res. 70, 245\u2013317 (2021)","journal-title":"J. Artif. Intell. Res."},{"key":"26_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2022.103841","volume":"316","author":"M Cooper","year":"2023","unstructured":"Cooper, M., Marques-Silva, J.: Tractability of explaining classifier decisions. Artif. Intell. 316, 103841 (2023)","journal-title":"Artif. Intell."},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Darwiche, A., Hirth, A.: On the reasons behind decisions. In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), pp. 712\u2013720 (2020)","DOI":"10.3233\/FAIA200158"},{"key":"26_CR9","unstructured":"Dhurandhar, A., Ramamurthy, K.N., Shanmugam, K.: Is this the right neighborhood? Accurate and query efficient model agnostic explanations. In: Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS) (2022)"},{"issue":"2","key":"26_CR10","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1137\/070684914","volume":"39","author":"V Feldman","year":"2009","unstructured":"Feldman, V., Gopalan, P., Khot, S., Ponnuswami, A.K.: On agnostic learning of parities, monomials, and halfspaces. SIAM J. Comput. 39(2), 606\u2013645 (2009)","journal-title":"SIAM J. Comput."},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Huang, X., Izza, Y., Ignatiev, A., Marques-Silva, J.: On efficiently explaining graph-based classifiers. In: Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 356\u2013367 (2021)","DOI":"10.24963\/kr.2021\/34"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Ignatiev, A.: Towards trustable explainable AI. In: Proceedings of the 29h International Joint Conference on Artificial Intelligence (IJCAI), pp. 5154\u20135158 (2020)","DOI":"10.24963\/ijcai.2020\/726"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Ignatiev, A., Izza, Y., Stuckey, P., Marques-Silva, J.: Using MaxSAT for efficient explanations of tree ensembles. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence, pp. 3776\u20133785 (2022)","DOI":"10.1609\/aaai.v36i4.20292"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Ignatiev, A., Narodytska, N., Marques-Silva, J.: Abduction-based explanations for machine learning models. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence, pp. 1511\u20131519 (2019)","DOI":"10.1609\/aaai.v33i01.33011511"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Ignatiev, A., Silva, J.M.: SAT-based rigorous explanations for decision lists. In: Proceedings of the 24th International Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 251\u2013269 (2021)","DOI":"10.1007\/978-3-030-80223-3_18"},{"key":"26_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2023.108939","volume":"159","author":"Y Izza","year":"2023","unstructured":"Izza, Y., Huang, X., Ignatiev, A., Narodytska, N., Cooper, M.C., Marques-Silva, J.: On computing probabilistic abductive explanations. Int. J. Approx. Reason. 159, 108939 (2023)","journal-title":"Int. J. Approx. Reason."},{"key":"26_CR17","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1613\/jair.1.13575","volume":"75","author":"Y Izza","year":"2022","unstructured":"Izza, Y., Ignatiev, A., Marques-Silva, J.: On tackling explanation redundancy in decision trees. J. Artif. Intell. Res. 75, 261\u2013321 (2022)","journal-title":"J. Artif. Intell. Res."},{"key":"26_CR18","unstructured":"Karimi, A., Barthe, G., Balle, B., Valera, I.: Model-agnostic counterfactual explanations for consequential decisions. In: Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR, vol.\u00a0108, pp. 895\u2013905 (2020)"},{"issue":"2\u20133","key":"26_CR19","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1023\/A:1022615600103","volume":"17","author":"MJ Kearns","year":"1994","unstructured":"Kearns, M.J., Schapire, R.E., Sellie, L.: Toward efficient agnostic learning. Mach. Learn. 17(2\u20133), 115\u2013141 (1994)","journal-title":"Mach. Learn."},{"key":"26_CR20","unstructured":"Koh, P.W., Liang, P.: Understanding black-box predictions via influence functions. In: Proceedings of the 34th International Conference on Machine Learning (ICML). Proceedings of Machine Learning Research, vol.\u00a070, pp. 1885\u20131894 (2017)"},{"key":"26_CR21","unstructured":"Lundberg, S.M., Lee, S.: A unified approach to interpreting model predictions. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017 (NeurIPS), pp. 4765\u20134774 (2017)"},{"key":"26_CR22","unstructured":"Marques-Silva, J., Gerspacher, T., Cooper, M., Ignatiev, A., Narodytska, N.: Explaining Naive Bayes and other linear classifiers with polynomial time and delay. In: Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020 (NeurIPS) (2020)"},{"issue":"2","key":"26_CR23","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1037\/h0043158","volume":"63","author":"GA Miller","year":"1956","unstructured":"Miller, G.A.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63(2), 81\u201397 (1956)","journal-title":"Psychol. Rev."},{"key":"26_CR24","unstructured":"Molnar, C.: Interpretable Machine Learning, 2nd edn. leanpub.com (2022). https:\/\/christophm.github.io\/interpretable-ml-book"},{"key":"26_CR25","unstructured":"Perron, L., Didier, F.: CP-SAT. https:\/\/developers.google.com\/optimization\/cp"},{"key":"26_CR26","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \u201cwhy should I trust you?\u201d: Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"26_CR27","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Anchors: high-precision model-agnostic explanations. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), pp. 1527\u20131535 (2018)","DOI":"10.1609\/aaai.v32i1.11491"},{"issue":"3","key":"26_CR28","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/S0895-7177(03)90083-5","volume":"38","author":"TL Saaty","year":"2003","unstructured":"Saaty, T.L., \u00d6zdemir, M.S.: Why the magic number seven plus or minus two. Math. Comput. Model. 38(3), 233\u2013244 (2003)","journal-title":"Math. Comput. Model."},{"key":"26_CR29","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107298019","volume-title":"Understanding Machine Learning: From Theory to Algorithms","author":"S Shalev-Shwartz","year":"2014","unstructured":"Shalev-Shwartz, S., Ben-David, S.: Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, Cambridge (2014)"},{"key":"26_CR30","doi-asserted-by":"crossref","unstructured":"Shih, A., Choi, A., Darwiche, A.: A symbolic approach to explaining Bayesian network classifiers. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), pp. 5103\u20135111 (2018)","DOI":"10.24963\/ijcai.2018\/708"},{"issue":"11","key":"26_CR31","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1145\/1968.1972","volume":"27","author":"LG Valiant","year":"1984","unstructured":"Valiant, L.G.: A theory of the learnable. Commun. ACM 27(11), 1134\u20131142 (1984)","journal-title":"Commun. ACM"},{"key":"26_CR32","first-page":"351","volume":"70","author":"S W\u00e4ldchen","year":"2021","unstructured":"W\u00e4ldchen, S., MacDonald, J., Hauch, S., Kutyniok, G.: The computational complexity of understanding binary classifier decisions. J. Artif. Intell. Res. 70, 351\u2013387 (2021)","journal-title":"J. Artif. Intell. Res."},{"key":"26_CR33","unstructured":"Zhao, X., Huang, W., Huang, X., Robu, V., Flynn, D.: BayLIME: Bayesian local interpretable model-agnostic explanations. In: Proceedings of the 37th International Conference on Uncertainty in Artificial Intelligence (UAI). PMLR, vol.\u00a0161, pp. 887\u2013896 (2021)"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Research Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70359-1_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T07:27:08Z","timestamp":1768202828000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70359-1_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031703584","9783031703591"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70359-1_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"22 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vilnius","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2024.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}