{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:27:36Z","timestamp":1740137256891,"version":"3.37.3"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:00:00Z","timestamp":1679443200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:00:00Z","timestamp":1679443200000},"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":["Quantum Inf Process"],"DOI":"10.1007\/s11128-023-03879-5","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T11:03:42Z","timestamp":1679483022000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Quantum average neighborhood margin maximization for feature extraction"],"prefix":"10.1007","volume":"22","author":[{"given":"Shang","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi-Jie","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guang-Bao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4040-2448","authenticated-orcid":false,"given":"Yu-Guang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,3,22]]},"reference":[{"key":"3879_CR1","unstructured":"Carreira-Perpin\u00e1n M.A.: A review of dimension reduction techniques. Department of Computer Science. University of Sheffield. Tech. Rep. CS-96\u201309 9(1\u201369), (1997)."},{"issue":"5500","key":"3879_CR2","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis, S.T., Saul, L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323\u20132326 (2000)","journal-title":"Science"},{"issue":"1\u20133","key":"3879_CR3","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","volume":"2","author":"S Wold","year":"1987","unstructured":"Wold, S., Esbensen, K., Geladi, P.: Principal component analysis. Chemometr. Intell. Lab. 2(1\u20133), 37\u201352 (1987)","journal-title":"Chemometr. Intell. Lab."},{"issue":"2","key":"3879_CR4","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1111\/j.1469-1809.1936.tb02137.x","volume":"7","author":"RA Fisher","year":"1936","unstructured":"Fisher, R.A.: The use of multiple measurements in taxonomic problems. Ann. Eugen. 7(2), 179\u2013188 (1936)","journal-title":"Ann. Eugen."},{"key":"3879_CR5","doi-asserted-by":"crossref","unstructured":"Wang F., Zhang C.: Feature extraction by maximizing the average neighborhood margin, in: 2007 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 2007, pp. 1\u20138.","DOI":"10.1109\/CVPR.2007.383124"},{"issue":"5","key":"3879_CR6","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1038\/nrn3475","volume":"14","author":"KS Button","year":"2013","unstructured":"Button, K.S., Ioannidis, J.P., Mokrysz, C., Nosek, B.A., Flint, J., Robinson, E.S., Munaf\u00f2, M.R.: Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neur. 14(5), 365\u2013376 (2013)","journal-title":"Nat. Rev. Neur."},{"key":"3879_CR7","unstructured":"Su\u00e1rez-D\u00edaz J.L., Garc\u00eda S., Herrera F.: A tutorial on distance metric learning: mathematical foundations, algorithms, experimental analysis, prospects and challenges (with appendices on mathematical background and detailed algorithms explanation). arXiv preprint arXiv:1812.05944 (2018)."},{"key":"3879_CR8","unstructured":"Shor P.W.: Algorithms for quantum computation: discrete logarithms and factoring, in: Proceedings 35th Annual Symposium on Foundations of Computer Science, IEEE, 1994, pp. 124\u2013134."},{"issue":"2","key":"3879_CR9","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1103\/PhysRevLett.79.325","volume":"79","author":"LK Grover","year":"1997","unstructured":"Grover, L.K.: Quantum mechanics helps in searching for a needle in a haystack. Phys. Rev. Lett. 79(2), 325 (1997)","journal-title":"Phys. Rev. Lett."},{"issue":"15","key":"3879_CR10","doi-asserted-by":"publisher","first-page":"150502","DOI":"10.1103\/PhysRevLett.103.150502","volume":"103","author":"AW Harrow","year":"2009","unstructured":"Harrow, A.W., Hassidim, A., Lloyd, S.: Quantum algorithm for linear systems of equations. Phys. Rev. Lett. 103(15), 150502 (2009)","journal-title":"Phys. Rev. Lett."},{"issue":"1","key":"3879_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/ncomms10138","volume":"7","author":"S Lloyd","year":"2016","unstructured":"Lloyd, S., Garnerone, S., Zanardi, P.: Quantum algorithms for topological and geometric analysis of data. Nat. Comm. 7(1), 1\u20137 (2016)","journal-title":"Nat. Comm."},{"issue":"3","key":"3879_CR12","doi-asserted-by":"publisher","first-page":"032301","DOI":"10.1103\/PhysRevA.96.032301","volume":"96","author":"BJ Duan","year":"2017","unstructured":"Duan, B.J., Yuan, J.B., Liu, Y., Li, D.: Quantum algorithm for support matrix machines. Phys. Rev. A 96(3), 032301 (2017)","journal-title":"Phys. Rev. A"},{"issue":"9","key":"3879_CR13","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1038\/nphys3029","volume":"10","author":"S Lloyd","year":"2014","unstructured":"Lloyd, S., Mohseni, M., Rebentrost, P.: Quantum principal component analysis. Nat. Phys. 10(9), 631\u2013633 (2014)","journal-title":"Nat. Phys."},{"issue":"8","key":"3879_CR14","first-page":"1","volume":"18","author":"CH Yu","year":"2019","unstructured":"Yu, C.H., Gao, F., Lin, S., Wang, J.: Quantum data compression by principal component analysis. Quan. Inf. Pro. 18(8), 1\u201320 (2019)","journal-title":"Quan. Inf. Pro."},{"issue":"6","key":"3879_CR15","doi-asserted-by":"publisher","first-page":"062403","DOI":"10.1103\/PhysRevA.102.062403","volume":"102","author":"X He","year":"2020","unstructured":"He, X.: Quantum subspace alignment for domain adaptation. Phys. Rev. A 102(6), 062403 (2020)","journal-title":"Phys. Rev. A"},{"issue":"3","key":"3879_CR16","doi-asserted-by":"publisher","first-page":"032410","DOI":"10.1103\/PhysRevA.102.032410","volume":"102","author":"X He","year":"2020","unstructured":"He, X.: Quantum correlation alignment for unsupervised domain adaptation. Phys. Rev. A 102(3), 032410 (2020)","journal-title":"Phys. Rev. A"},{"issue":"2","key":"3879_CR17","doi-asserted-by":"publisher","first-page":"129501","DOI":"10.1007\/s11432-021-3400-3","volume":"66","author":"S Gao","year":"2023","unstructured":"Gao, S., Pan, S.J., Yang, Y.G.: Quantum algorithm for kernelized correlation filter. Sci. China Inf. Sci. 66(2), 129501 (2023)","journal-title":"Sci. China Inf. Sci."},{"issue":"2","key":"3879_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2023.128587","volume":"615","author":"S Gao","year":"2023","unstructured":"Gao, S., Yang, Y.G.: New quantum algorithm for visual tracking. Physica A 615(2), 128587 (2023)","journal-title":"Physica A"},{"issue":"4","key":"3879_CR19","doi-asserted-by":"publisher","first-page":"042311","DOI":"10.1103\/PhysRevA.94.042311","volume":"94","author":"CH Yu","year":"2016","unstructured":"Yu, C.H., Gao, F., Wang, Q.L., Wen, Q.Y.: Quantum algorithm for association rules mining. Phys. Rev. A 94(4), 042311 (2016)","journal-title":"Phys. Rev. A"},{"issue":"3","key":"3879_CR20","doi-asserted-by":"publisher","first-page":"032311","DOI":"10.1103\/PhysRevA.99.032311","volume":"99","author":"BJ Duan","year":"2019","unstructured":"Duan, B.J., Yuan, J.B., Xu, J., Li, D.: Quantum algorithm and quantum circuit for a-optimal projection: dimensionality reduction. Phys. Rev. A 99(3), 032311 (2019)","journal-title":"Phys. Rev. A"},{"issue":"9","key":"3879_CR21","first-page":"1","volume":"19","author":"X He","year":"2020","unstructured":"He, X., Sun, L., Lyu, C., Wang, X.: Quantum locally linear embedding for nonlinear dimensionality reduction. Quan. Inf. Pro. 19(9), 1\u201321 (2020)","journal-title":"Quan. Inf. Pro."},{"issue":"5","key":"3879_CR22","doi-asserted-by":"publisher","first-page":"052402","DOI":"10.1103\/PhysRevA.102.052402","volume":"102","author":"SJ Pan","year":"2020","unstructured":"Pan, S.J., Wan, L.C., Liu, H.L., Wang, Q.L., Qin, S.J., Wen, Q.Y., Gao, F.: Improved quantum algorithm for A-optimal projection. Phys. Rev. A 102(5), 052402 (2020)","journal-title":"Phys. Rev. A"},{"key":"3879_CR23","unstructured":"Yu, K., Guo, G.D., Lin, S.: Quantum dimensionality reduction by linear discriminant analysis. arXiv preprint arXiv:2103.03131 (2021)."},{"issue":"1","key":"3879_CR24","doi-asserted-by":"publisher","first-page":"010001","DOI":"10.1088\/1402-4896\/aca4a8","volume":"98","author":"S Gao","year":"2023","unstructured":"Gao, S., Yang, Y.G.: A novel quantum recommender system. Phys. Scr. 98(1), 010001 (2023)","journal-title":"Phys. Scr."},{"key":"3879_CR25","unstructured":"Kerenidis I., Prakash A.: Quantum recommendation systems. arXiv preprint arXiv:1603.08675 (2016)."},{"key":"3879_CR26","first-page":"415","volume":"2017","author":"FG Brandao","year":"2017","unstructured":"Brandao, F.G., Svore, K.M.: Quantum speed-ups for solving semidefinite programs, in, IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS). IEEE 2017, 415\u2013426 (2017)","journal-title":"IEEE"},{"issue":"6","key":"3879_CR27","doi-asserted-by":"publisher","first-page":"062322","DOI":"10.1103\/PhysRevA.97.062322","volume":"97","author":"LC Wan","year":"2018","unstructured":"Wan, L.C., Yu, C.H., Pan, S.J., Gao, F., Wen, Q.Y., Qin, S.J.: Asymptotic quantum algorithm for the Toeplitz systems. Phys. Rev. A 97(6), 062322 (2018)","journal-title":"Phys. Rev. A"},{"key":"3879_CR28","doi-asserted-by":"publisher","DOI":"10.1088\/1674-1056\/acb914","author":"S Gao","year":"2023","unstructured":"Gao, S., Yang, Y.G.: Quantum algorithm for Toeplitz matrix-vector multiplication. Chin. Phys. B (2023). https:\/\/doi.org\/10.1088\/1674-1056\/acb914","journal-title":"Chin. Phys. B"},{"issue":"7","key":"3879_CR29","doi-asserted-by":"publisher","first-page":"073023","DOI":"10.1088\/1367-2630\/ab2a9e","volume":"21","author":"P Rebentrost","year":"2019","unstructured":"Rebentrost, P., Schuld, M., Wossnig, L., Petruccione, F., Lloyd, S.: Quantum gradient descent and Newton\u2019s method for constrained polynomial optimization. New J. Phys. 21(7), 073023 (2019)","journal-title":"New J. Phys."},{"issue":"12","key":"3879_CR30","doi-asserted-by":"publisher","first-page":"eaat9004","DOI":"10.1126\/sciadv.aat9004","volume":"4","author":"X Gao","year":"2018","unstructured":"Gao, X., Zhang, Z.Y., Duan, L.M.: A quantum machine learning algorithm based on generative models. Sci. Adv. 4(12), eaat9004 (2018)","journal-title":"Sci. Adv."},{"issue":"1","key":"3879_CR31","doi-asserted-by":"publisher","first-page":"eaav2761","DOI":"10.1126\/sciadv.aav2761","volume":"5","author":"L Hu","year":"2019","unstructured":"Hu, L., Wu, S.H., Cai, W., Ma, Y., Mu, X., Xu, Y., Wang, H., Song, Y., Deng, D.L., Zou, C.L.: Quantum generative adversarial learning in a superconducting quantum circuit. Sci. Adv. 5(1), eaav2761 (2019)","journal-title":"Sci. Adv."},{"issue":"11","key":"3879_CR32","doi-asserted-by":"publisher","first-page":"2863","DOI":"10.1016\/j.patcog.2009.04.015","volume":"42","author":"F Wang","year":"2009","unstructured":"Wang, F., Wang, X., Zhang, D., Zhang, C., Li, T.: Marginface: A novel face recognition method by average neighborhood margin maximization. Patt. Rec. 42(11), 2863\u20132875 (2009)","journal-title":"Patt. Rec."},{"key":"3879_CR33","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V.: Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"16","key":"3879_CR34","doi-asserted-by":"publisher","first-page":"160501","DOI":"10.1103\/PhysRevLett.100.160501","volume":"100","author":"V Giovannetti","year":"2008","unstructured":"Giovannetti, V., Lloyd, S., Maccone, L.: Quantum random access memory. Phys. Rev. Lett. 100(16), 160501 (2008)","journal-title":"Phys. Rev. Lett."},{"key":"3879_CR35","unstructured":"Kerenidis I., Landman J., Luongo A., Prakash A.: q-means: A quantum algorithm for unsupervised machine learning. arXiv preprint arXiv:1812.03584 (2018)."},{"key":"3879_CR36","doi-asserted-by":"crossref","unstructured":"Pan S.J., Wan L.C., Liu H.L., Wu Y.S., Qin S.J., Wen Q.Y., Gao F.: Quantum algorithm for Neighborhood Preserving Embedding. arXiv preprint arXiv:2110.11541 (2021).","DOI":"10.1088\/1674-1056\/ac523a"},{"issue":"13","key":"3879_CR37","doi-asserted-by":"publisher","first-page":"130503","DOI":"10.1103\/PhysRevLett.113.130503","volume":"113","author":"P Rebentrost","year":"2014","unstructured":"Rebentrost, P., Mohseni, M., Lloyd, S.: Quantum support vector machine for big data classification. Phys. Rev. Lett. 113(13), 130503 (2014)","journal-title":"Phys. Rev. Lett."},{"issue":"1","key":"3879_CR38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41534-016-0002-2","volume":"3","author":"S Kimmel","year":"2017","unstructured":"Kimmel, S., Lin, C.Y.Y., Low, G.H., Ozols, M., Yoder, T.J.: Hamiltonian simulation with optimal sample complexity. npj Quan. Inf. 3(1), 1\u20137 (2017)","journal-title":"npj Quan. Inf."},{"key":"3879_CR39","unstructured":"Chakraborty S., Gily\u00e9n A., Jeffery S.: The power of block-encoded matrix powers: improved regression techniques via faster Hamiltonian simulation. arXiv preprint arXiv:1804.01973 (2018)."},{"key":"3879_CR40","doi-asserted-by":"crossref","unstructured":"Gily\u00e9n A., Su Y., Low G.H., Wiebe N.: Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics, in: Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019, pp. 193\u2013204.","DOI":"10.1145\/3313276.3316366"},{"key":"3879_CR41","doi-asserted-by":"publisher","first-page":"163","DOI":"10.22331\/q-2019-07-12-163","volume":"3","author":"GH Low","year":"2019","unstructured":"Low, G.H., Chuang, I.L.: Hamiltonian simulation by qubitization. Quantum 3, 163 (2019)","journal-title":"Quantum"},{"issue":"7","key":"3879_CR42","doi-asserted-by":"publisher","DOI":"10.1088\/1367-2630\/18\/7\/073011","volume":"18","author":"I Cong","year":"2016","unstructured":"Cong, I., Duan, L.M.: Quantum discriminant analysis for dimensionality reduction and classification. New J. Phys. 18(7), 073011 (2016)","journal-title":"New J. Phys."}],"container-title":["Quantum Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11128-023-03879-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11128-023-03879-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11128-023-03879-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,8]],"date-time":"2023-04-08T14:22:38Z","timestamp":1680963758000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11128-023-03879-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,22]]},"references-count":42,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["3879"],"URL":"https:\/\/doi.org\/10.1007\/s11128-023-03879-5","relation":{},"ISSN":["1573-1332"],"issn-type":[{"type":"electronic","value":"1573-1332"}],"subject":[],"published":{"date-parts":[[2023,3,22]]},"assertion":[{"value":"20 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethics Committee approval was obtained from the Institutional Ethics Committee of Beijing University of Technology to the commencement of the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"152"}}