{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T18:31:25Z","timestamp":1776882685494,"version":"3.51.2"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031781063","type":"print"},{"value":"9783031781070","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"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\/978-3-031-78107-0_13","type":"book-chapter","created":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T19:31:29Z","timestamp":1733081489000},"page":"201-214","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Privacy-Preserving Ensemble Learning Using Fully Homomorphic Encryption"],"prefix":"10.1007","author":[{"given":"Tilak","family":"Sharma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nalini","family":"Ratha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charanjit","family":"Jutla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Dietterich, T.G.: Ensemble methods in machine learning. In: Proceedings of the First International Workshop on Multiple Classifier Systems, ser. MCS \u201900. Berlin, Heidelberg: Springer-Verlag, pp. 1\u201315 (2000)","DOI":"10.1007\/3-540-45014-9_1"},{"key":"13_CR2","unstructured":"Kumar, J., Singh, A.K., Mohan, A., Buyya, R.: Ensemble learning. In: Encyclopedia of Biometrics (2019). https:\/\/api.semanticscholar.org\/CorpusID:9963037"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Sabahi, F.: Cloud computing security threats and responses. In: 2011 IEEE 3rd International Conference on Communication Software and Networks, pp. 245\u2013249 (2011)","DOI":"10.1109\/ICCSN.2011.6014715"},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"02","DOI":"10.1007\/s11227-012-0831-5","volume":"63","author":"C Modi","year":"2013","unstructured":"Modi, C., Patel, D., Borisaniya, B., Patel, A., Rajarajan, M.: A survey on security issues and solutions at different layers of cloud computing. J. Supercomput. 63, 02 (2013)","journal-title":"J. Supercomput."},{"key":"13_CR5","unstructured":"Papernot, N., McDaniel, P., Sinha, A., Wellman, M.: Towards the science of security and privacy in machine learning (2016). https:\/\/arxiv.org\/abs\/1611.03814"},{"key":"13_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1007\/978-3-319-70694-8_15","volume-title":"Advances in Cryptology \u2013 ASIACRYPT 2017","author":"JH Cheon","year":"2017","unstructured":"Cheon, J.H., Kim, A., Kim, M., Song, Y.: Homomorphic encryption for arithmetic of approximate numbers. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10624, pp. 409\u2013437. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-70694-8_15"},{"key":"13_CR7","unstructured":"Lakshminarayanan, B., Pritzel, A., Blundell, C.: Simple and scalable predictive uncertainty estimation using deep ensembles. In: Advances in Neural Information Processing Systems, Guyon, I. (eds.) vol.\u00a030. Curran Associates, Inc. (2017). https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/file\/9ef2ed4b7fd2c810847ffa5fa85bce38-Paper.pdf"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Seijo-Pardo, B., Porto-D\u00edaz, I., Bol\u00f3n-Canedo, V., Alonso-Betanzos, A.: Ensemble feature selection: homogeneous and heterogeneous approaches. Knowl. Based Syst. 118, 124\u2013139 (2017). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0950705116304749","DOI":"10.1016\/j.knosys.2016.11.017"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Delgado, R.: A semi-hard voting combiner scheme to ensemble multi-class probabilistic classifiers. Appl. Intell. 52, 3653\u20133677 (2022)","DOI":"10.1007\/s10489-021-02447-7"},{"issue":"1","key":"13_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-020-00299-5","volume":"7","author":"IK Nti","year":"2020","unstructured":"Nti, I.K., Adekoya, A.F., Weyori, B.A.: A comprehensive evaluation of ensemble learning for stock-market prediction. J. Big Data 7(1), 1\u201340 (2020). https:\/\/doi.org\/10.1186\/s40537-020-00299-5","journal-title":"J. Big Data"},{"issue":"3","key":"13_CR11","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1093\/pan\/mps002","volume":"20","author":"JM Montgomery","year":"2012","unstructured":"Montgomery, J.M., Hollenbach, F.M., Ward, M.D.: Improving predictions using ensemble bayesian model averaging. Polit. Anal. 20(3), 271\u2013291 (2012)","journal-title":"Polit. Anal."},{"issue":"7","key":"13_CR12","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.micpro.2004.02.006","volume":"28","author":"G-R Latif-Shabgahi","year":"2004","unstructured":"Latif-Shabgahi, G.-R.: A novel algorithm for weighted average voting used in fault tolerant computing systems. Microprocess. Microsyst. 28(7), 357\u2013361 (2004)","journal-title":"Microprocess. Microsyst."},{"issue":"3","key":"13_CR13","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0230671","volume":"15","author":"BM Hopkinson","year":"2020","unstructured":"Hopkinson, B.M., King, A.C., Owen, D.P., Johnson-Roberson, M., Long, M.H., Bhandarkar, S.M.: Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks. PLoS ONE 15(3), e0230671 (2020)","journal-title":"PLoS ONE"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Khan, W., Ghazanfar, M.A., Azam, M.A., Karami, A., Alyoubi, K.H., Alfakeeh, A.S.: Stock market prediction using machine learning classifiers and social media, news. J. Ambient Intell. Humanized Comput. 13, 1\u201324 (2020)","DOI":"10.1007\/s12652-020-01839-w"},{"key":"13_CR15","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1023\/B:MACH.0000015879.28004.9b","volume":"54","author":"C Soares","year":"2004","unstructured":"Soares, C., Brazdil, P.B., Kuba, P.: A meta-learning method to select the kernel width in support vector regression. Mach. Learn. 54, 195\u2013209 (2004)","journal-title":"Mach. Learn."},{"issue":"9","key":"13_CR16","first-page":"7271","volume":"34","author":"S Kuruvayil","year":"2022","unstructured":"Kuruvayil, S., Palaniswamy, S.: Emotion recognition from facial images with simultaneous occlusion, pose and illumination variations using meta-learning. J. King Saud Univ. Comput. Inf. Sci. 34(9), 7271\u20137282 (2022)","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"issue":"9","key":"13_CR17","first-page":"5149","volume":"44","author":"T Hospedales","year":"2021","unstructured":"Hospedales, T., Antoniou, A., Micaelli, P., Storkey, A.: Meta-learning in neural networks: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(9), 5149\u20135169 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"13_CR18","doi-asserted-by":"publisher","first-page":"6240","DOI":"10.1002\/int.22549","volume":"36","author":"JP Monteiro","year":"2021","unstructured":"Monteiro, J.P., Ramos, D., Carneiro, D., Duarte, F., Fernandes, J.M., Novais, P.: Meta-learning and the new challenges of machine learning. Int. J. Intell. Syst. 36(11), 6240\u20136272 (2021)","journal-title":"Int. J. Intell. Syst."},{"key":"13_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106940","volume":"220","author":"F Haghighi","year":"2021","unstructured":"Haghighi, F., Omranpour, H.: Stacking ensemble model of deep learning and its application to Persian\/Arabic handwritten digits recognition. Knowl. Based Syst. 220, 106940 (2021)","journal-title":"Knowl. Based Syst."},{"key":"13_CR20","unstructured":"Gong, X., et al.: Federated learning with privacy-preserving ensemble attention distillation (2022)"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Basak, J., Kate, K., Tyagi, V., Ratha, N.: QPLC: a novel multimodal biometric score fusion method. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, vol. 2010, pp. 46\u201352 (2010)","DOI":"10.1109\/CVPRW.2010.5543232"},{"key":"13_CR22","unstructured":"Cheon, J.H., Kim, D., Kim, D., Lee, H.H., Lee, K.: Numerical method for comparison on homomorphically encrypted numbers. Cryptology ePrint Archive, Paper 2019\/417 (2019). https:\/\/eprint.iacr.org\/2019\/417, https:\/\/eprint.iacr.org\/2019\/417"},{"issue":"1","key":"13_CR23","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/s41597-022-01721-8","volume":"10","author":"J Yang","year":"2023","unstructured":"Yang, J., et al.: MedMNIST V2-a large-scale lightweight benchmark for 2D and 3D biomedical image classification. Sci. Data 10(1), 41 (2023)","journal-title":"Sci. Data"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78107-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T20:04:27Z","timestamp":1733083467000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78107-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,2]]},"ISBN":["9783031781063","9783031781070"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78107-0_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,2]]},"assertion":[{"value":"2 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 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":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}