{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T07:05:39Z","timestamp":1763535939221,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030937355"},{"type":"electronic","value":"9783030937362"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-93736-2_11","type":"book-chapter","created":{"date-parts":[[2022,2,17]],"date-time":"2022-02-17T21:02:28Z","timestamp":1645131748000},"page":"119-127","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Differentially Private Learning from Label Proportions"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0347-5760","authenticated-orcid":false,"given":"Timon","family":"Sachweh","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6856-9848","authenticated-orcid":false,"given":"Daniel","family":"Boiar","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9841-1101","authenticated-orcid":false,"given":"Thomas","family":"Liebig","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,17]]},"reference":[{"key":"11_CR1","doi-asserted-by":"publisher","unstructured":"Bonawitz, K., et al.: Practical secure aggregation for privacy-preserving machine learning. In: Thuraisingham, B.M., Evans, D., Malkin, T., Xu, D. (eds.) Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30\u201303 November, 2017, pp. 1175\u20131191. ACM (2017). https:\/\/doi.org\/10.1145\/3133956.3133982","DOI":"10.1145\/3133956.3133982"},{"key":"11_CR2","unstructured":"Buitinck, L., et al.: API design for machine learning software: experiences from the scikit-learn project. In: ECML PKDD Workshop: Languages for Data Mining and Machine Learning, pp. 108\u2013122 (2013)"},{"key":"11_CR3","doi-asserted-by":"publisher","unstructured":"Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci. 9(3-4), 211\u2013407 (2014). https:\/\/doi.org\/10.1561\/0400000042","DOI":"10.1561\/0400000042"},{"key":"11_CR4","doi-asserted-by":"publisher","unstructured":"Fan, H., Liu, Y., Zeng, Z.: Decentralized privacy-preserving data aggregation scheme for smart grid based on blockchain. Sensors 20(18), 5282 (2020). https:\/\/doi.org\/10.3390\/s20185282","DOI":"10.3390\/s20185282"},{"issue":"6","key":"11_CR5","doi-asserted-by":"publisher","first-page":"703","DOI":"10.2501\/IJMR-2017-050","volume":"59","author":"M Goddard","year":"2017","unstructured":"Goddard, M.: The EU general data protection regulation (GDPR): European regulation that has a global impact. Int. J. Mark. Res. 59(6), 703\u2013705 (2017)","journal-title":"Int. J. Mark. Res."},{"key":"11_CR6","unstructured":"Grama, M., Musat, M., Mu\u00f1oz-Gonz\u00e1lez, L., Passerat-Palmbach, J., Rueckert, D., Alansary, A.: Robust aggregation for adaptive privacy preserving federated learning in healthcare. CoRR abs\/2009.08294 (2020). https:\/\/arxiv.org\/abs\/2009.08294"},{"key":"11_CR7","doi-asserted-by":"publisher","unstructured":"Groat, M.M., He, W., Forrest, S.: KIPDA: k-indistinguishable privacy-preserving data aggregation in wireless sensor networks. In: INFOCOM 2011. 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 10\u201315 April 2011, Shanghai, China, pp. 2024\u20132032. IEEE (2011). https:\/\/doi.org\/10.1109\/INFCOM.2011.5935010","DOI":"10.1109\/INFCOM.2011.5935010"},{"key":"11_CR8","doi-asserted-by":"publisher","unstructured":"He, W., Liu, X., Nguyen, H., Nahrstedt, K., Abdelzaher, T.F.: PDA: privacy-preserving data aggregation in wireless sensor networks. In: INFOCOM 2007. 26th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 6\u201312 May 2007, Anchorage, Alaska, USA, pp. 2045\u20132053. IEEE (2007). https:\/\/doi.org\/10.1109\/INFCOM.2007.237","DOI":"10.1109\/INFCOM.2007.237"},{"key":"11_CR9","unstructured":"McCann, B.: A review of scats operation and deployment in Dublin. In: Proceedings of the 19th JCT Traffic Signal Symposium & Exhibition (2014)"},{"key":"11_CR10","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR11","doi-asserted-by":"publisher","unstructured":"Shi, J., Zhang, R., Liu, Y., Zhang, Y.: Prisense: privacy-preserving data aggregation in people-centric urban sensing systems. In: INFOCOM 2010. 29th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 15\u201319 March 2010, San Diego, CA, USA, pp. 758\u2013766. IEEE (2010). https:\/\/doi.org\/10.1109\/INFCOM.2010.5462147","DOI":"10.1109\/INFCOM.2010.5462147"},{"key":"11_CR12","unstructured":"Stolpe, M., Liebig, T., Morik, K.: Communication-efficient learning of traffic flow in a network of wireless presence sensors. In: Proceedings of the Workshop on Parallel and Distributed Computing for Knowledge Discovery in Data Bases (PDCKDD 2015) (2015)"},{"key":"11_CR13","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/978-3-642-23808-6_23","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"M Stolpe","year":"2011","unstructured":"Stolpe, M., Morik, K.: Learning from label proportions by optimizing cluster model selection. In: Gunopulos, D., Hofmann, T., Malerba, D., Vazirgiannis, M. (eds.) ECML PKDD 2011. LNCS (LNAI), vol. 6913, pp. 349\u2013364. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-23808-6_23"},{"key":"11_CR14","doi-asserted-by":"publisher","unstructured":"Zhang, J., Zhao, Y., Wu, J., Chen, B.: LVPDA: a lightweight and verifiable privacy-preserving data aggregation scheme for edge-enabled IoT. IEEE Internet Things J. 7(5), 4016\u20134027 (2020). https:\/\/doi.org\/10.1109\/JIOT.2020.2978286","DOI":"10.1109\/JIOT.2020.2978286"},{"key":"11_CR15","doi-asserted-by":"publisher","unstructured":"Zhang, W.: Secure data aggregation. In: van Tilborg, H.C.A., Jajodia, S. (eds.) Encyclopedia of Cryptography and Security, 2nd edn., pp. 1104\u20131105. Springer (2011). https:\/\/doi.org\/10.1007\/978-1-4419-5906-5_639","DOI":"10.1007\/978-1-4419-5906-5_639"},{"key":"11_CR16","doi-asserted-by":"publisher","unstructured":"Zhang, X., Liu, X., Yu, J., Dang, N., Qi, X., Zhang, Q.: Energy-efficient privacy preserving data aggregation protocols based on slicing. In: 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), iThings\/GreenCom\/CPSCom\/SmartData 2019, Atlanta, GA, USA, July 14\u201317, 2019, pp. 546\u2013551. IEEE (2019). https:\/\/doi.org\/10.1109\/iThings\/GreenCom\/CPSCom\/SmartData.2019.00109","DOI":"10.1109\/iThings\/GreenCom\/CPSCom\/SmartData.2019.00109"}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-93736-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T02:12:14Z","timestamp":1651803134000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-93736-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030937355","9783030937362"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-93736-2_11","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"17 February 2022","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":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2021.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"869","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"210","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-9","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}