{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T19:41:03Z","timestamp":1774381263703,"version":"3.50.1"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031789762","type":"print"},{"value":"9783031789779","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-78977-9_11","type":"book-chapter","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T10:12:44Z","timestamp":1737972764000},"page":"167-182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Soft Hoeffding Tree: A Transparent and\u00a0Differentiable Model on\u00a0Data Streams"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3967-0891","authenticated-orcid":false,"given":"Kirsten","family":"K\u00f6bschall","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3420-551X","authenticated-orcid":false,"given":"Lisa","family":"Hartung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0136-2540","authenticated-orcid":false,"given":"Stefan","family":"Kramer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,28]]},"reference":[{"issue":"8","key":"11_CR1","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","volume":"35","author":"Y Bengio","year":"2013","unstructured":"Bengio, Y., Courville, A., Vincent, P.: Representation learning: a review and new perspectives. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 1798\u20131828 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Bifet, A., Gavald\u00e0, R.: Adaptive learning from evolving data streams. In: Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII, pp. 249\u2013260. IDA, Springer-Verlag (2009)","DOI":"10.1007\/978-3-642-03915-7_22"},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Bifet, A., Holmes, G., Pfahringer, B., Frank, E.: Fast perceptron decision tree learning from evolving data streams. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 299\u2013310. Springer-Verlag (2010)","DOI":"10.1007\/978-3-642-13672-6_30"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Bifet, A., Pfahringer, B., Read, J., Holmes, G.: Efficient data stream classification via probabilistic adaptive windows. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing, pp. 801\u2013806. SAC, Association for Computing Machinery (2013)","DOI":"10.1145\/2480362.2480516"},{"key":"11_CR5","unstructured":"Breiman, L., Friedman, J., Stone, C., Olshen, R.: Classification and Regression Trees. Chapman and Hall\/CRC (1984)"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Domingos, P., Hulten, G.: Mining high-speed data streams. In: Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 71\u201380. KDD, Association for Computing Machinery (2000)","DOI":"10.1145\/347090.347107"},{"key":"11_CR7","unstructured":"Doshi-Velez, F., Kim, B.: Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608 (2017)"},{"key":"11_CR8","unstructured":"Frosst, N., Hinton, G.E.: Distilling a neural network into a soft decision tree. In: Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA). CEUR Workshop Proceedings, vol.\u00a02071. CEUR-WS.org (2017)"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Gomes, H.M., et al.: Adaptive random forests for evolving data stream classification. Mach. Learn. 106(9\u201310), 1469\u20131495 (2017)","DOI":"10.1007\/s10994-017-5642-8"},{"key":"11_CR10","unstructured":"Gouk, H., Pfahringer, B., Frank, E.: Stochastic gradient trees. In: Proceedings of The Eleventh Asian Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a0101, pp. 1094\u20131109. PMLR (2019)"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Gunasekara, N., Gomes, H.M., Pfahringer, B., Bifet, A.: Online hyperparameter optimization for streaming neural networks, pp.\u00a01\u20139 (2022)","DOI":"10.1109\/IJCNN55064.2022.9891953"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Gunasekara, N., Gomes, H.M., Pfahringer, B., Bifet, A.: Online hyperparameter optimization for streaming neural networks. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp.\u00a01\u20139 (2022)","DOI":"10.1109\/IJCNN55064.2022.9891953"},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Gunasekara, N., Pfahringer, B., Gomes, H.M., Bifet, A.: Survey on online streaming continual learning. In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI, pp. 6628\u20136637. International Joint Conferences on Artificial Intelligence Organization (2023)","DOI":"10.24963\/ijcai.2023\/743"},{"key":"11_CR14","unstructured":"Hazimeh, H., Ponomareva, N., Mol, P., Tan, Z., Mazumder, R.: The tree ensemble layer: differentiability meets conditional computation. In: Proceedings of the 37th International Conference on Machine Learning. ICML, JMLR.org (2020)"},{"key":"11_CR15","doi-asserted-by":"publisher","first-page":"997","DOI":"10.1007\/s11263-019-01237-6","volume":"128","author":"T Hehn","year":"2020","unstructured":"Hehn, T., Kooij, J., Hamprecht, F.: End-to-end learning of decision trees and forests. Int. J. Comput. Vision 128, 997\u20131011 (2020)","journal-title":"Int. J. Comput. Vision"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Holmes, G., Kirkby, R., Pfahringer, B.: Stress-testing hoeffding trees. In: Knowledge Discovery in Databases: PKDD, pp. 495\u2013502. Springer-Verlag (2005)","DOI":"10.1007\/11564126_50"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Hulten, G., Spencer, L., Domingos, P.: Mining time-changing data streams. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 97\u2013106. KDD, Association for Computing Machinery (2001)","DOI":"10.1145\/502512.502529"},{"key":"11_CR18","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: Proceedings of the 32nd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a037, pp. 448\u2013456. PMLR (2015)"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Jordan, M., Jacobs, R.: Hierarchical mixtures of experts and the EM algorithm. In: Proceedings of 1993 International Conference on Neural Networks (IJCNN), vol.\u00a02, pp. 1339\u20131344 (1993)","DOI":"10.1109\/IJCNN.1993.716791"},{"key":"11_CR20","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations (ICLR) (2015)"},{"key":"11_CR21","unstructured":"Kontschieder, P., Fiterau, M., Criminisi, A., Bul\u00f2, S.R.: Deep neural decision forests. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp. 4190\u20134194. IJCAI, AAAI Press (2016)"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Lipton, Z.: The mythos of model interpretability. Commun. ACM 61 (2016)","DOI":"10.1145\/3233231"},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Manapragada, C., Webb, G.I., Salehi, M.: Extremely fast decision tree. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1953\u20131962. KDD, Association for Computing Machinery (2018)","DOI":"10.1145\/3219819.3220005"},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Olson, R., La\u00a0Cava, W., Orzechowski, P., Urbanowicz, R., Moore, J.: PMLB: a large benchmark suite for machine learning evaluation and comparison. BioData Mining 10 (2017)","DOI":"10.1186\/s13040-017-0154-4"},{"key":"11_CR25","unstructured":"Oza, N.C., Russell, S.J.: Online bagging and boosting. In: Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics. Proceedings of Machine Learning Research, vol.\u00a0R3, pp. 229\u2013236. PMLR (2001)"},{"key":"11_CR26","unstructured":"Paszke, A., et al.: PyTorch: an imperative style, high-performance deep learning library. Curran Associates Inc. (2019)"},{"issue":"6","key":"11_CR27","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1109\/TKDE.2012.66","volume":"25","author":"L Rutkowski","year":"2013","unstructured":"Rutkowski, L., Pietruczuk, L., Duda, P., Jaworski, M.: Decision trees for mining data streams based on the mcdiarmid\u2019s bound. IEEE Trans. Knowl. Data Eng. 25(6), 1272\u20131279 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"11_CR28","unstructured":"Xu, L., Skoularidou, M., Cuesta-Infante, A., Veeramachaneni, K.: Modeling Tabular Data Using Conditional GAN. Curran Associates Inc. (2019)"},{"key":"11_CR29","unstructured":"\u0130rsoy, O., Y\u0131ld\u0131z, O.T., Alpayd\u0131n, E.: Soft decision trees. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR), pp. 1819\u20131822 (2012)"}],"container-title":["Lecture Notes in Computer Science","Discovery Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78977-9_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T10:13:08Z","timestamp":1737972788000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78977-9_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031789762","9783031789779"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78977-9_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"28 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Discovery Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pisa","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"14 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dis2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ds2024.isti.cnr.it\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}