{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T16:31:55Z","timestamp":1762014715462,"version":"build-2065373602"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"33","license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["KAKENHI 23K18489"],"award-info":[{"award-number":["KAKENHI 23K18489"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s00521-025-11603-w","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T15:40:05Z","timestamp":1758037205000},"page":"27883-27900","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Toward transfer learning integrating multiple functions through the latent space"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9440-1467","authenticated-orcid":false,"given":"Haruka","family":"Iwai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ichiro","family":"Kobayashi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"11603_CR1","unstructured":"Gaier A, Ha D, Wallach H, et al. (Curran Associates, Inc., 2019) (eds) Weight agnostic neural networks. (eds Wallach, H. et\u00a0al.) Advances in Neural Information Processing Systems, Vol.\u00a032. https:\/\/proceedings.neurips.cc\/paper\/2019\/file\/e98741479a7b998f8 8b8f8c9f0b6b6f1-Paper.pdf"},{"key":"11603_CR2","unstructured":"Kusner MJ, Paige B, Hern\u00e1ndez-Lobato, JM (2017) Grammar variational autoencoder. https:\/\/arxiv.org\/abs\/1703.01925"},{"key":"11603_CR3","unstructured":"Zoph B, Le Q (2017) Neural architecture search with reinforcement learning. https:\/\/arxiv.org\/abs\/1611.01578"},{"key":"11603_CR4","doi-asserted-by":"crossref","unstructured":"Zoph B, Vasudevan V, Shlens J, Le QV (2018) Learning transferable architectures for scalable image recognition, 8697\u20138710. https:\/\/doi.ieeecomputersociety.org\/10.1109\/CVPR.2018.00907","DOI":"10.1109\/CVPR.2018.00907"},{"key":"11603_CR5","unstructured":"Pham H, Guan M, Zoph B, Le Q, Dean J, Dy J, Krause A (PMLR, 2018) (eds) Efficient neural architecture search via parameters sharing. (eds Dy, J. & Krause, A.) Proceedings of the 35th international conference on machine learning, Vol.\u00a080 of proceedings of machine learning research, 4095\u20134104. https:\/\/proceedings.mlr.press\/v80\/pham18a.html"},{"key":"11603_CR6","doi-asserted-by":"crossref","unstructured":"Chatzianastasis M, Dasoulas G, Siolas G, Vazirgiannis M (2021) Graph-based neural architecture search with operation embeddings. arXiv:2105.04885","DOI":"10.1109\/ICCVW54120.2021.00048"},{"key":"11603_CR7","unstructured":"Schlichtkrull M, et al. (2017) Modeling relational data with graph convolutional networks. https:\/\/api.semanticscholar.org\/CorpusID:5458500"},{"key":"11603_CR8","unstructured":"Rao X, Zhao B, Yi X, Liu D (2022) Cr-lso: convex neural architecture optimization in the latent space of graph variational autoencoder with input convex neural networks. arXiv:2211.05950"},{"key":"11603_CR9","unstructured":"Li J, Liu Y, Liu J, Wang W (2020) Neural architecture optimization with graph vae. arXiv:2006.10310"},{"key":"11603_CR10","doi-asserted-by":"crossref","unstructured":"Lukasik J, Friede D, Zela A, Hutter F, Keuper M (2021) Smooth variational graph embeddings for efficient neural architecture search, 1\u20138","DOI":"10.1109\/IJCNN52387.2021.9534092"},{"key":"11603_CR11","unstructured":"Tian Q, Arbel T, Clark JJ (2020) Deep discriminant analysis for task-dependent compact network search. ArXiv arXiv:2009.13716. https:\/\/api.semanticscholar.org\/CorpusID:221995750"},{"key":"11603_CR12","doi-asserted-by":"publisher","first-page":"928","DOI":"10.1109\/TEVC.2021.3097937","volume":"25","author":"Y-W Wen","year":"2021","unstructured":"Wen Y-W, Peng S-H, Ting C-K (2021) Two-stage evolutionary neural architecture search for transfer learning. IEEE Trans Evol Comput 25:928\u2013940","journal-title":"IEEE Trans Evol Comput"},{"key":"11603_CR13","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss K, Khoshgoftaar TM, Wang D (2016) A survey of transfer learning. Journal of Big Data 3:9. https:\/\/doi.org\/10.1186\/s40537-016-0043-6","journal-title":"Journal of Big Data"},{"key":"11603_CR14","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan SJ, Yang Q (2010) A survey on transfer learning. IEEE Trans Knowl Data Eng 22:1345\u20131359","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"11603_CR15","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","volume":"109","author":"F Zhuang","year":"2021","unstructured":"Zhuang F et al (2021) A comprehensive survey on transfer learning. Proc IEEE 109:43\u201376","journal-title":"Proc IEEE"},{"key":"11603_CR16","unstructured":"Zenke F, Poole B, Ganguli S, Precup D, Teh YW (PMLR, 2017) (eds) Continual learning through synaptic intelligence. (eds Precup, D. & Teh, Y.\u00a0W.) Proceedings of the 34th international conference on machine learning, Vol.\u00a070 of proceedings of machine learning research, 3987\u20133995. https:\/\/proceedings.mlr.press\/v70\/zenke17a.html"},{"key":"11603_CR17","first-page":"3366","volume":"44","author":"M De Lange","year":"2022","unstructured":"De Lange M et al (2022) A continual learning survey: defying forgetting in classification tasks. IEEE Trans Pattern Anal Mach Intell 44:3366\u20133385","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11603_CR18","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1023\/A:1007379606734","volume":"28","author":"R Caruana","year":"1997","unstructured":"Caruana R (1997) Multitask learning. Mach Learn 28:41\u201375. https:\/\/doi.org\/10.1023\/A:1007379606734","journal-title":"Mach Learn"},{"key":"11603_CR19","doi-asserted-by":"publisher","first-page":"5586","DOI":"10.1109\/TKDE.2021.3070203","volume":"34","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Yang Q (2022) A survey on multi-task learning. IEEE Trans Knowl Data Eng 34:5586\u20135609","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"11603_CR20","unstructured":"Fifty C, et\u00a0al. (Curran Associates, Inc., 2021) Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. & Vaughan, J.\u00a0W. (eds) Efficiently identifying task groupings for multi-task learning. (eds Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. & Vaughan, J.\u00a0W.) Advances in neural information processing systems, Vol.\u00a034, 27503\u201327516. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2021\/file\/e77910ebb93b511588557806310f78f1-Paper.pdf"},{"key":"11603_CR21","doi-asserted-by":"crossref","unstructured":"Han L, Zhang Y (2015) Learning multi-level task groups in multi-task learning. Proceedings of the AAAI conference on artificial intelligence29. https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/9581","DOI":"10.1609\/aaai.v29i1.9581"},{"key":"11603_CR22","doi-asserted-by":"crossref","unstructured":"Almudaifer AI, et al (2024) Transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection. arXiv e-printsarXiv:2401.15222","DOI":"10.1186\/s13326-024-00311-4"},{"key":"11603_CR23","doi-asserted-by":"publisher","first-page":"16085","DOI":"10.1609\/aaai.v38i14.29541","volume":"38","author":"Y Xin","year":"2024","unstructured":"Xin Y, Du J, Wang Q, Lin Z, Yan K (2024) Vmt-adapter: parameter-efficient transfer learning for multi-task dense scene understanding. Proceedings of the AAAI conference on artificial intelligence 38:16085\u201316093 (https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/29541)","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"11603_CR24","unstructured":"Qin Y, Wang X, Zhang Z, Chen H, Zhu W, Oh A, et al (Curran Associates, Inc., 2023) (eds) Multi-task graph neural architecture search with task-aware collaboration and curriculum. (eds Oh, A. et\u00a0al.) Advances in neural information processing systems, Vol.\u00a036, 24879\u201324891. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/file\/4e839c9c398c58c878a394633b806ccd-Paper-Conference.pdf"},{"key":"11603_CR25","unstructured":"Wu B, et al (2021) Fbnetv5: Neural architecture search for multiple tasks in one run. CoRR. arXiv:2111.10007"},{"key":"11603_CR26","doi-asserted-by":"crossref","unstructured":"Gao Y, et al (2020) Mtl-nas: task-agnostic neural architecture search towards general-purpose multi-task learning","DOI":"10.1109\/CVPR42600.2020.01156"},{"key":"11603_CR27","doi-asserted-by":"crossref","unstructured":"Du X, El-Khamy M, Lee J, Davis LS (2016) Fused dnn: a deep neural network fusion approach to fast and robust pedestrian detection. 2017 IEEE winter conference on applications of computer vision (WACV) 953\u2013961","DOI":"10.1109\/WACV.2017.111"},{"key":"11603_CR28","unstructured":"Ho J, Jain A, Abbeel P (Curran Associates, Inc., 2020) Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. & Lin, H. (eds) Denoising diffusion probabilistic models. (eds Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. & Lin, H.) Advances in neural information processing systems, Vol.\u00a033, 6840\u20136851 . https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2020\/file\/4c5bcfec8584af0d967f1ab10179ca4b-Paper.pdf"},{"key":"11603_CR29","unstructured":"Goodfellow I, et al (Curran Associates, Inc., 2014) Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. & Weinberger, K. (eds) Generative adversarial nets. (eds Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. & Weinberger, K.) Advances in neural information processing systems, Vol.\u00a027. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2014\/file\/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf"},{"key":"11603_CR30","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J (Curran Associates, Inc., 2013) in Distributed representations of words and phrases and their compositionality (eds Burges, C., Bottou, L., Welling, M., Ghahramani, Z. & Weinberger, K.) Advances in neural information processing systems, Vol.\u00a026 3111\u20133119"},{"key":"11603_CR31","unstructured":"Kingma DP, Welling M (2014) Auto-encoding variational bayes. arXiv:1312.6114v10."},{"key":"11603_CR32","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1109\/MSP.2012.2211477","volume":"29","author":"L Deng","year":"2012","unstructured":"Deng L (2012) The mnist database of handwritten digit images for machine learning research. IEEE Signal Process Mag 29:141\u2013142","journal-title":"IEEE Signal Process Mag"},{"key":"11603_CR33","unstructured":"AdityaDutt. Multicolor-shapes-database. Github (version: commit 4ac0c56a944bbd88dc68807dba6ab3ed669292a0). https:\/\/github.com\/AdityaDutt\/MultiColor-Shapes-Database"},{"key":"11603_CR34","volume-title":"k-means++: the advantages of careful seeding, 1027\u20131035","author":"D Arthur","year":"2007","unstructured":"Arthur D, Vassilvitskii S (2007) k-means++: the advantages of careful seeding, 1027\u20131035. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA"},{"key":"11603_CR35","unstructured":"Rosenberg A, Hirschberg J (Association for Computational Linguistics, Prague, Czech Republic, 2007) Eisner, J. (ed.) V-measure: a conditional entropy-based external cluster evaluation measure. (ed.Eisner, J.) Proceedings of the 2007 joint conference on empirical methods in natural language processing and computational natural language learning (EMNLP-CoNLL), 410\u2013420. https:\/\/aclanthology.org\/D07-1043"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11603-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-025-11603-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11603-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T16:27:55Z","timestamp":1762014475000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-025-11603-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,16]]},"references-count":35,"journal-issue":{"issue":"33","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["11603"],"URL":"https:\/\/doi.org\/10.1007\/s00521-025-11603-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2025,9,16]]},"assertion":[{"value":"29 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest associated with this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}