{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T01:40:14Z","timestamp":1768441214570,"version":"3.49.0"},"reference-count":90,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T00:00:00Z","timestamp":1670976000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T00:00:00Z","timestamp":1670976000000},"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":["Int J Comput Vis"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s11263-022-01709-2","type":"journal-article","created":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T09:03:05Z","timestamp":1671008585000},"page":"732-751","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Shuffled Linear Regression with Outliers in Both Covariates and Responses"],"prefix":"10.1007","volume":"131","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2585-506X","authenticated-orcid":false,"given":"Feiran","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2205-6115","authenticated-orcid":false,"given":"Kent","family":"Fujiwara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7595-1300","authenticated-orcid":false,"given":"Fumio","family":"Okura","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1935-4752","authenticated-orcid":false,"given":"Yasuyuki","family":"Matsushita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,14]]},"reference":[{"key":"1709_CR1","doi-asserted-by":"crossref","unstructured":"Abid, A., & Zou, J. (2018). A stochastic expectation-maximization approach to shuffled linear regression. In Proceedings of annual allerton conference on communication, control, and computing.","DOI":"10.1109\/ALLERTON.2018.8635907"},{"key":"1709_CR2","unstructured":"Abid, A., Poon, A., & Zou, J. (2017). Linear regression with shuffled labels. ArXiv Preprint ArXiv:1705.01342."},{"key":"1709_CR3","doi-asserted-by":"crossref","unstructured":"Aoki, Y., Goforth, H., Srivatsan, R.A., & Lucey, S. (2019). Pointnetlk: Robust & efficient point cloud registration using pointnet. In Proceedings of conference on computer vision and pattern recognition (CVPR), pp. 7163\u20137172.","DOI":"10.1109\/CVPR.2019.00733"},{"key":"1709_CR4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1987.4767965","author":"KS Arun","year":"1987","unstructured":"Arun, K. S., Huang, T. S., & Blostein, S. D. (1987). Least-squares fitting of two 3-d point sets. Transactions on Pattern Analysis and Machine Intelligence. https:\/\/doi.org\/10.1109\/TPAMI.1987.4767965.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"1709_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s10107-007-0133-5","volume":"116","author":"H Attouch","year":"2009","unstructured":"Attouch, H., & Bolte, J. (2009). On the convergence of the proximal algorithm for nonsmooth functions involving analytic features. Mathematical Programming, 116(1), 5\u201316.","journal-title":"Mathematical Programming"},{"issue":"2","key":"1709_CR6","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1287\/moor.1100.0449","volume":"35","author":"H Attouch","year":"2010","unstructured":"Attouch, H., Bolte, J., Redont, P., & Soubeyran, A. (2010). Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the kurdyka-\u0142ojasiewicz inequality. Mathematics of Operations Research, 35(2), 438\u2013457.","journal-title":"Mathematics of Operations Research"},{"key":"1709_CR7","doi-asserted-by":"crossref","unstructured":"Aubry, M., Schlickewei, U., & Cremers, D. (2011). The wave kernel signature: A quantum mechanical approach to shape analysis. In Proceedings of international conference on computer vision workshops (ICCV workshops).","DOI":"10.1109\/ICCVW.2011.6130444"},{"issue":"1","key":"1709_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.disc.2007.12.043","volume":"309","author":"J Bell","year":"2009","unstructured":"Bell, J., & Stevens, B. (2009). A survey of known results and research areas for n-queens. Discrete Mathematics, 309(1), 1\u201331.","journal-title":"Discrete Mathematics"},{"key":"1709_CR9","doi-asserted-by":"crossref","unstructured":"Birdal, T., & Simsekli, U. (2019). Probabilistic permutation synchronization using the riemannian structure of the birkhoff polytope. In Proceedings of conference on computer vision and pattern recognition (CVPR), pp. 11,105\u201311,116.","DOI":"10.1109\/CVPR.2019.01136"},{"key":"1709_CR10","doi-asserted-by":"crossref","unstructured":"Bogo, F., Romero, J., Loper, M., & Black, M.J. (2014). FAUST: Dataset and evaluation for 3D mesh registration. In Proceedings of conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2014.491"},{"issue":"4","key":"1709_CR11","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.1137\/050644641","volume":"17","author":"J Bolte","year":"2007","unstructured":"Bolte, J., Daniilidis, A., & Lewis, A. (2007). The \u0142ojasiewicz inequality for nonsmooth subanalytic functions with applications to subgradient dynamical systems. SIAM Journal on Optimization, 17(4), 1205\u20131223.","journal-title":"SIAM Journal on Optimization"},{"issue":"1","key":"1709_CR12","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s10107-013-0701-9","volume":"146","author":"J Bolte","year":"2014","unstructured":"Bolte, J., Sabach, S., & Teboulle, M. (2014). Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Mathematical Programming, 146(1), 459\u2013494.","journal-title":"Mathematical Programming"},{"key":"1709_CR13","doi-asserted-by":"crossref","unstructured":"Bronstein, A.M., Bronstein, M.M., & Kimmel, R. (2008). Numerical geometry of non-rigid shapes.","DOI":"10.1007\/978-0-387-73301-2"},{"key":"1709_CR14","doi-asserted-by":"crossref","unstructured":"Cai, Z., Chin, T.J., Le, H., & Suter, D. (2018) Deterministic consensus maximization with biconvex programming. In Proceedings of European conference on computer vision (ECCV), pp. 685\u2013700.","DOI":"10.1007\/978-3-030-01258-8_42"},{"key":"1709_CR15","doi-asserted-by":"crossref","unstructured":"Campbell, D., & Petersson, L. (2015). An adaptive data representation for robust point-set registration and merging. In Proceedings of international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2015.488"},{"key":"1709_CR16","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1109\/ICPR.2002.1047997","volume":"3","author":"D Chetverikov","year":"2002","unstructured":"Chetverikov, D., Svirko, D., Stepanov, D., & Krsek, P. (2002). The trimmed iterative closest point algorithm. Object Recognition Supported by User Interaction for Service Robots, 3, 545\u2013548.","journal-title":"Object Recognition Supported by User Interaction for Service Robots"},{"issue":"2","key":"1709_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-01818-3","volume":"7","author":"TJ Chin","year":"2017","unstructured":"Chin, T. J., & Suter, D. (2017). The maximum consensus problem: Recent algorithmic advances. Synthesis Lectures on Computer Vision, 7(2), 1\u2013194.","journal-title":"Synthesis Lectures on Computer Vision"},{"key":"1709_CR18","doi-asserted-by":"crossref","unstructured":"Choi, S., Kim, T., & Yu, W. (2009) Performance evaluation of RANSAC family. In Proceedings of British machine vision conference (BMVC).","DOI":"10.5244\/C.23.81"},{"key":"1709_CR19","doi-asserted-by":"crossref","unstructured":"Curless, B., & Levoy, M. (1996). A volumetric method for building complex models from range images. In Proceedings of annual conference on computer graphics and interactive techniques.","DOI":"10.1145\/237170.237269"},{"key":"1709_CR20","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.parco.2016.05.012","volume":"57","author":"K Date","year":"2016","unstructured":"Date, K., & Nagi, R. (2016). Gpu-accelerated hungarian algorithms for the linear assignment problem. Parallel Computing, 57, 52\u201372.","journal-title":"Parallel Computing"},{"issue":"107","key":"1709_CR21","first-page":"254","volume":"147","author":"D De Menezes","year":"2021","unstructured":"De Menezes, D., Prata, D. M., Secchi, A. R., & Pinto, J. C. (2021). A review on robust m-estimators for regression analysis. Computers & Chemical Engineering, 147(107), 254.","journal-title":"Computers & Chemical Engineering"},{"key":"1709_CR22","unstructured":"Doornik, J.A. (2011). Robust estimation using least trimmed squares. Tech. rep., Institute for Economic Modelling, Oxford Martin School, and Economics Department, University of Oxford, UK."},{"key":"1709_CR23","doi-asserted-by":"crossref","unstructured":"Eckart, B., Kim, K., & Jan, K. (2018). Eoe: Expected overlap estimation over unstructured point cloud data. In Proceedings of international conference on 3D vision (3DV), pp. 747\u2013755.","DOI":"10.1109\/3DV.2018.00090"},{"key":"1709_CR24","doi-asserted-by":"crossref","unstructured":"Elhami, G., Scholefield, A., Haro, B.B., & Vetterli, M. (2017). Unlabeled sensing: Reconstruction algorithm and theoretical guarantees. In Proceedings of international conference on acoustics, speech, and signal processing (ICASSP), pp. 4566\u20134570.","DOI":"10.1109\/ICASSP.2017.7953021"},{"key":"1709_CR25","unstructured":"Fiori, M., Sprechmann, P., Vogelstein, J., Mus\u00e9, P., & Sapiro, G. (2013). Robust multimodal graph matching: Sparse coding meets graph matching. In Proceedings of conference on neural information processing systems (NIPS)."},{"issue":"6","key":"1709_CR26","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M. A., & Bolles, R. C. (1981). Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381\u2013395.","journal-title":"Communications of the ACM"},{"key":"1709_CR27","unstructured":"Fogel, F., Jenatton, R., Bach, F., & d\u2019Aspremont, A. (2013). Convex relaxations for permutation problems. In Proceedings of conference on neural information processing systems (NIPS)."},{"key":"1709_CR28","doi-asserted-by":"crossref","unstructured":"Gao, W., & Tedrake, R. (2019). Filterreg: Robust and efficient probabilistic point-set registration using gaussian filter and twist parameterization. In Proceedings of conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2019.01135"},{"issue":"8","key":"1709_CR29","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1016\/S0031-3203(98)80010-1","volume":"31","author":"S Gold","year":"1998","unstructured":"Gold, S., Rangarajan, A., Lu, C. P., Pappu, S., & Mjolsness, E. (1998). New algorithms for 2d and 3d point matching: Pose estimation and correspondence. Pattern Recognition, 31(8), 1019\u20131031.","journal-title":"Pattern Recognition"},{"key":"1709_CR30","first-page":"2049","volume":"6","author":"A Gunawardana","year":"2005","unstructured":"Gunawardana, A., & Byrne, W. (2005). Convergence theorems for generalized alternating minimization procedures. Journal of Machine Learning Research, 6, 2049\u20132073.","journal-title":"Journal of Machine Learning Research"},{"issue":"5","key":"1709_CR31","doi-asserted-by":"publisher","first-page":"1242","DOI":"10.1109\/TSP.2017.2786276","volume":"66","author":"S Haghighatshoar","year":"2017","unstructured":"Haghighatshoar, S., & Caire, G. (2017). Signal recovery from unlabeled samples. Transactions on Signal Processing, 66(5), 1242\u20131257.","journal-title":"Transactions on Signal Processing"},{"key":"1709_CR32","doi-asserted-by":"crossref","unstructured":"Hahnel, D., Burgard, W., Fox, D., Fishkin, K., & Philipose, M. (2004). Mapping and localization with rfid technology. In Proceedings of international conference on robotics and automation (ICRA), vol.\u00a01, pp. 1015\u20131020.","DOI":"10.1109\/ROBOT.2004.1307283"},{"key":"1709_CR33","doi-asserted-by":"crossref","unstructured":"Hampel, F. (2014). Robust inference. Statistics Reference Online.","DOI":"10.1002\/9781118445112.stat07417"},{"key":"1709_CR34","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1080\/00401706.1985.10488027","volume":"27","author":"FR Hampel","year":"1985","unstructured":"Hampel, F. R. (1985). The breakdown points of the mean combined with some rejection rules. Technometrics, 27, 95\u2013107.","journal-title":"Technometrics"},{"key":"1709_CR35","doi-asserted-by":"crossref","unstructured":"Hartley, R., & Zisserman, A. (2003). Multiple view geometry in computer vision.","DOI":"10.1017\/CBO9780511811685"},{"issue":"2","key":"1709_CR36","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/0167-9473(92)00070-8","volume":"17","author":"DM Hawkins","year":"1994","unstructured":"Hawkins, D. M. (1994). The feasible solution algorithm for least trimmed squares regression. Computational Statistics & Data Analysis, 17(2), 185\u2013196.","journal-title":"Computational Statistics & Data Analysis"},{"key":"1709_CR37","unstructured":"Hsu, D.J., Shi, K., & Sun, X. (2017) Linear regression without correspondence. In Proceedings of conference on neural information processing systems (NIPS)."},{"key":"1709_CR38","doi-asserted-by":"crossref","unstructured":"Huber, P.J. (1992). Robust estimation of a location parameter. In Breakthroughs in statistics, pp. 492\u2013518.","DOI":"10.1007\/978-1-4612-4380-9_35"},{"issue":"2","key":"1709_CR39","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s11263-015-0858-1","volume":"117","author":"K Jia","year":"2016","unstructured":"Jia, K., Chan, T. H., Zeng, Z., Gao, S., Wang, G., Zhang, T., & Ma, Y. (2016). Roml: A robust feature correspondence approach for matching objects in a set of images. International Journal of Computer Vision, 117(2), 173\u2013197.","journal-title":"International Journal of Computer Vision"},{"issue":"7","key":"1709_CR40","doi-asserted-by":"publisher","first-page":"1339","DOI":"10.1109\/TPAMI.2010.212","volume":"33","author":"H Jiang","year":"2010","unstructured":"Jiang, H., Stella, X. Y., & Martin, D. R. (2010). Linear scale and rotation invariant matching. Transactions on Pattern Analysis and Machine Intelligence, 33(7), 1339\u20131355.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1709_CR41","doi-asserted-by":"crossref","unstructured":"Kuhn, A., & Mayer, H. (2015). Incremental division of very large point clouds for scalable 3d surface reconstruction. In Proceedings of international conference on computer vision workshops (ICCV workshops).","DOI":"10.1109\/ICCVW.2015.30"},{"issue":"1\u20132","key":"1709_CR42","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1002\/nav.3800020109","volume":"2","author":"HW Kuhn","year":"1955","unstructured":"Kuhn, H. W. (1955). The hungarian method for the assignment problem. Naval Research Logistics Quarterly, 2(1\u20132), 83\u201397.","journal-title":"Naval Research Logistics Quarterly"},{"issue":"2","key":"1709_CR43","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1023\/A:1006529012972","volume":"13","author":"P Larranaga","year":"1999","unstructured":"Larranaga, P., Kuijpers, C. M. H., Murga, R. H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13(2), 129\u2013170.","journal-title":"Artificial Intelligence Review"},{"key":"1709_CR44","doi-asserted-by":"crossref","unstructured":"Le, H., Chin, T.J., & Suter, D. (2017) An exact penalty method for locally convergent maximum consensus. In Proceedings of conference on computer vision and pattern recognition (CVPR), pp. 1888\u20131896.","DOI":"10.1109\/CVPR.2017.48"},{"issue":"3","key":"1709_CR45","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1109\/TPAMI.2019.2939307","volume":"43","author":"H Le","year":"2019","unstructured":"Le, H., Chin, T. J., Eriksson, A., Do, T. T., & Suter, D. (2019). Deterministic approximate methods for maximum consensus robust fitting. Transactions on Pattern Analysis and Machine Intelligence, 43(3), 842\u2013857.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1709_CR46","doi-asserted-by":"crossref","unstructured":"Li, H., & Hartley, R. (2007). The 3d-3d registration problem revisited. In Proceedings of international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2007.4409077"},{"key":"1709_CR47","doi-asserted-by":"crossref","unstructured":"Li, F., Fujiwara, k., Okura, F., & Matsushita, Y. (2021). Generalized shuffled linear regression. In Proceedings of international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV48922.2021.00641"},{"key":"1709_CR48","doi-asserted-by":"crossref","unstructured":"Lian, W., & Zhang, L. (2014). Point matching in the presence of outliers in both point sets: A concave optimization approach. In Proceedings of conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2014.52"},{"issue":"5","key":"1709_CR49","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MSP.2020.3003845","volume":"37","author":"J Li","year":"2020","unstructured":"Li, J., So, A. M. C., & Ma, W. K. (2020). Understanding notions of stationarity in nonsmooth optimization: A guided tour of various constructions of subdifferential for nonsmooth functions. Signal Processing Magazine, 37(5), 18\u201331.","journal-title":"Signal Processing Magazine"},{"key":"1709_CR50","doi-asserted-by":"crossref","unstructured":"Lowe, D.G. (1999). Object recognition from local scale-invariant features. In Proceedings of international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.1999.790410"},{"issue":"1","key":"1709_CR51","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1137\/0210002","volume":"10","author":"A Lubiw","year":"1981","unstructured":"Lubiw, A. (1981). Some np-complete problems similar to graph isomorphism. SIAM Journal on Computing, 10(1), 11\u201321.","journal-title":"SIAM Journal on Computing"},{"issue":"2","key":"1709_CR52","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1109\/TPAMI.2003.1177151","volume":"25","author":"J Maciel","year":"2003","unstructured":"Maciel, J., & Costeira, J. P. (2003). A global solution to sparse correspondence problems. Transactions on Pattern Analysis and Machine Intelligence, 25(2), 187\u2013199.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1709_CR53","doi-asserted-by":"crossref","unstructured":"Marques, M., Sto\u0161i\u0107, M., & Costeira, J. (2009). Subspace matching: Unique solution to point matching with geometric constraints. In Proceedings of international conference on computer vision (ICCV), pp. 1288\u20131294.","DOI":"10.1109\/ICCV.2009.5459318"},{"key":"1709_CR54","doi-asserted-by":"crossref","unstructured":"Maset, E., Arrigoni, F., & Fusiello, A. (2017). Practical and efficient multi-view matching. In Proceedings of international conference on computer vision (ICCV), pp. 4568\u20134576.","DOI":"10.1109\/ICCV.2017.489"},{"key":"1709_CR55","unstructured":"Mathias, R. (2006). The Linear Algebra a Beginning Graduate Student Ought to Know."},{"key":"1709_CR56","doi-asserted-by":"crossref","unstructured":"Melzi, S., Ren, J., Rodol\u00e0, E., Sharma, A., Wonka, P., & Ovsjanikov, M. (2019). Zoomout: Spectral upsampling for efficient shape correspondence. Transactions on Graphics, 38(6).","DOI":"10.1145\/3355089.3356524"},{"key":"1709_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2019.103837","volume":"24","author":"IS Mohamed","year":"2019","unstructured":"Mohamed, I. S., Capitanelli, A., Mastrogiovanni, F., Rovetta, S., & Zaccaria, R. (2019). A 2d laser rangefinder scans dataset of standard eur pallets. Data in brief, 24, 103837.","journal-title":"Data in brief"},{"issue":"12","key":"1709_CR58","doi-asserted-by":"publisher","first-page":"2262","DOI":"10.1109\/TPAMI.2010.46","volume":"32","author":"A Myronenko","year":"2010","unstructured":"Myronenko, A., & Song, X. (2010). Point set registration: Coherent point drift. Transactions on Pattern Analysis and Machine Intelligence, 32(12), 2262\u20132275.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1709_CR59","doi-asserted-by":"crossref","unstructured":"Narayanan, A., & Shmatikov, V. (2008). Robust de-anonymization of large sparse datasets. In Proceedings of symposium on security and privacy.","DOI":"10.1109\/SP.2008.33"},{"key":"1709_CR60","doi-asserted-by":"crossref","unstructured":"Nejatbakhsh, A., & Varol, E. (2021). Neuron matching in c. elegans with robust approximate linear regression without correspondence. In Proceedings of winter conference on applications of computer vision (WACV).","DOI":"10.1109\/WACV48630.2021.00288"},{"key":"1709_CR61","doi-asserted-by":"crossref","unstructured":"Ovsjanikov, M., Ben-Chen, M., Solomon, J., Butscher, A., & Guibas, L. (2012). Functional maps: A flexible representation of maps between shapes. Transactions on Graphics, 31(4).","DOI":"10.1145\/2185520.2185526"},{"key":"1709_CR62","unstructured":"Pachauri, D., Kondor, R., & Singh, V. (2013). Solving the multi-way matching problem by permutation synchronization. In Proceedings of conference on neural information processing systems (NIPS), vol. 26."},{"key":"1709_CR63","doi-asserted-by":"crossref","unstructured":"Pananjady, A., Wainwright, M.J., & Courtade, T.A. (2017). Denoising linear models with permuted data. In Proceedings of international symposium on information theory (ISIT).","DOI":"10.1109\/ISIT.2017.8006567"},{"issue":"5","key":"1709_CR64","doi-asserted-by":"publisher","first-page":"3286","DOI":"10.1109\/TIT.2017.2776217","volume":"64","author":"A Pananjady","year":"2017","unstructured":"Pananjady, A., Wainwright, M. J., & Courtade, T. A. (2017). Linear regression with shuffled data: Statistical and computational limits of permutation recovery. Transactions on Information Theory, 64(5), 3286\u20133300.","journal-title":"Transactions on Information Theory"},{"issue":"14","key":"1709_CR65","doi-asserted-by":"publisher","first-page":"1705","DOI":"10.1177\/0278364912458814","volume":"31","author":"F Pomerleau","year":"2012","unstructured":"Pomerleau, F., Liu, M., Colas, F., & Siegwart, R. (2012). Challenging data sets for point cloud registration algorithms. International Journal of Robotics Research, 31(14), 1705\u20131711.","journal-title":"International Journal of Robotics Research"},{"key":"1709_CR66","doi-asserted-by":"crossref","unstructured":"Pylv\u00e4n\u00e4inen, T., Berclaz, J., Korah, T., Hedau, V., Aanjaneya, M., & Grzeszczuk, R. (2012). 3d city modeling from street-level data for augmented reality applications. In Proceedings of international conference on 3D imaging, modeling, processing, visualization & transmission, pp. 238\u2013245.","DOI":"10.1109\/3DIMPVT.2012.19"},{"issue":"6","key":"1709_CR67","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3272127.3275040","volume":"37","author":"J Ren","year":"2018","unstructured":"Ren, J., Poulenard, A., Wonka, P., & Ovsjanikov, M. (2018). Continuous and orientation-preserving correspondences via functional maps. Transactions on Graphics, 37(6), 1\u20136.","journal-title":"Transactions on Graphics"},{"key":"1709_CR68","unstructured":"Rousseeuw, P.J., & Leroy, A.M. (2005). Robust regression and outlier detection."},{"key":"1709_CR69","doi-asserted-by":"crossref","unstructured":"Rusinkiewicz, S. (2019). A symmetric objective function for icp. Transactions on Graphics, 38(4).","DOI":"10.1145\/3306346.3323037"},{"key":"1709_CR70","doi-asserted-by":"crossref","unstructured":"Rusu, R.B., Blodow, N., & Beetz, M. (2009). Fast point feature histograms (fpfh) for 3d registration. In Proceedings of international conference on robotics and automation (ICRA).","DOI":"10.1109\/ROBOT.2009.5152473"},{"key":"1709_CR71","doi-asserted-by":"crossref","unstructured":"Shiratori, T., Berclaz, J., Harville, M., Shah, C., Li, T., Matsushita, Y., & Shiller, S. (2015). Efficient large-scale point cloud registration using loop closures. In Proceedings of international conference on 3D vision (3DV), pp. 232\u2013240.","DOI":"10.1109\/3DV.2015.33"},{"issue":"1","key":"1709_CR72","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1214\/18-EJS1498","volume":"13","author":"M Slawski","year":"2019","unstructured":"Slawski, M., Ben-David, E., et al. (2019). Linear regression with sparsely permuted data. Electronic Journal of Statistics, 13(1), 1\u201336.","journal-title":"Electronic Journal of Statistics"},{"issue":"204","key":"1709_CR73","first-page":"1","volume":"21","author":"M Slawski","year":"2019","unstructured":"Slawski, M., Ben-David, E., & Li, P. (2019). A two-stage approach to multivariate linear regression with sparsely mismatched data. Journal of Machine Learning Research, 21(204), 1\u201342.","journal-title":"Journal of Machine Learning Research"},{"issue":"1","key":"1709_CR74","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.laa.2010.08.028","volume":"434","author":"M Sto\u0161i\u0107","year":"2011","unstructured":"Sto\u0161i\u0107, M., Marques, M., & Costeira, J. P. (2011). Convex solution of a permutation problem. Linear Algebra and its Applications, 434(1), 361\u2013369.","journal-title":"Linear Algebra and its Applications"},{"key":"1709_CR75","doi-asserted-by":"publisher","first-page":"173","DOI":"10.5194\/isprsannals-I-3-173-2012","volume":"3","author":"P Theiler","year":"2012","unstructured":"Theiler, P., Schindler, K., et al. (2012). Automatic registration of terrestrial laser scanner point clouds using natural planar surfaces. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3, 173\u2013178.","journal-title":"ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences"},{"key":"1709_CR76","unstructured":"Tsakiris, M., & Peng, L. (2019). Homomorphic sensing. In Proceedings of international conference on machine learning (ICML)."},{"issue":"5","key":"1709_CR77","doi-asserted-by":"publisher","first-page":"3237","DOI":"10.1109\/TIT.2018.2809002","volume":"64","author":"J Unnikrishnan","year":"2018","unstructured":"Unnikrishnan, J., Haghighatshoar, S., & Vetterli, M. (2018). Unlabeled sensing with random linear measurements. Transactions on Information Theory, 64(5), 3237\u20133253.","journal-title":"Transactions on Information Theory"},{"key":"1709_CR78","doi-asserted-by":"crossref","unstructured":"Vestner, M., L\u00e4hner, Z., Boyarski, A., Litany, O., Slossberg, R., Remez, T., Rodola, E., Bronstein, A., Bronstein, M., & Kimmel, R., et\u00a0al. (2017). Efficient deformable shape correspondence via kernel matching. In Proceedings of international conference on 3D vision (3DV).","DOI":"10.1109\/3DV.2017.00065"},{"issue":"2","key":"1709_CR79","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1016\/S0377-2217(03)00205-4","volume":"157","author":"A Volgenant","year":"2004","unstructured":"Volgenant, A. (2004). Solving the k-cardinality assignment problem by transformation. European Journal of Operational Research, 157(2), 322\u2013331.","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"1709_CR80","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1109\/TPAMI.2018.2826536","volume":"41","author":"J Vongkulbhisal","year":"2018","unstructured":"Vongkulbhisal, J., De la Torre, F., & Costeira, J. P. (2018). Discriminative optimization: Theory and applications to computer vision. Transactions on Pattern Analysis and Machine Intelligence, 41(4), 829\u2013843.","journal-title":"Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1709_CR81","doi-asserted-by":"crossref","unstructured":"Wang, F., Xue, N., Yu, J.G., & Xia, G.S. (2020). Zero-assignment constraint for graph matching with outliers. In Proceedings of conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR42600.2020.00310"},{"key":"1709_CR82","unstructured":"Wu, Z., Song, S., Khosla, A., Yu, F., Zhang, L., Tang, X., & Xiao, J. (2015). 3d shapenets: A deep representation for volumetric shapes. In Proceedings of conference on computer vision and pattern recognition (CVPR), pp. 1912\u20131920."},{"issue":"3","key":"1709_CR83","doi-asserted-by":"publisher","first-page":"1758","DOI":"10.1137\/120887795","volume":"6","author":"Y Xu","year":"2013","unstructured":"Xu, Y., & Yin, W. (2013). A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion. SIAM Journal on Imaging Sciences, 6(3), 1758\u20131789.","journal-title":"SIAM Journal on Imaging Sciences"},{"issue":"2","key":"1709_CR84","doi-asserted-by":"publisher","first-page":"700","DOI":"10.1007\/s10915-017-0376-0","volume":"72","author":"Y Xu","year":"2017","unstructured":"Xu, Y., & Yin, W. (2017). A globally convergent algorithm for nonconvex optimization based on block coordinate update. Journal of Scientific Computing, 72(2), 700\u2013734.","journal-title":"Journal of Scientific Computing"},{"key":"1709_CR85","doi-asserted-by":"crossref","unstructured":"Yadav, S.S., Lopes, P.A.C., Ilic, A., & Patra, S.K. (2019). Hungarian algorithm for subcarrier assignment problem using gpu and cuda. International Journal of Communication Systems, 32(4).","DOI":"10.1002\/dac.3884"},{"issue":"2","key":"1709_CR86","doi-asserted-by":"publisher","first-page":"3519","DOI":"10.1214\/18-EJS1470","volume":"12","author":"E Yang","year":"2018","unstructured":"Yang, E., Lozano, A. C., & Aravkin, A. (2018). A general family of trimmed estimators for robust high-dimensional data analysis. Electronic Journal of Statistics, 12(2), 3519\u20133553.","journal-title":"Electronic Journal of Statistics"},{"issue":"2","key":"1709_CR87","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1109\/TRO.2020.3033695","volume":"37","author":"H Yang","year":"2020","unstructured":"Yang, H., Shi, J., & Carlone, L. (2020). Teaser: Fast and certifiable point cloud registration. Transactions on Robotics, 37(2), 314\u2013333.","journal-title":"Transactions on Robotics"},{"key":"1709_CR88","unstructured":"Zangwill, W.I. (1969). Nonlinear programming: a unified approach."},{"key":"1709_CR89","doi-asserted-by":"crossref","unstructured":"Zhang, H., Slawski, M., & Li, P. (2019). Permutation recovery from multiple measurement vectors in unlabeled sensing. In Proceedings of international symposium on information theory (ISIT).","DOI":"10.1109\/ISIT.2019.8849447"},{"key":"1709_CR90","doi-asserted-by":"crossref","unstructured":"Zhou, Q.Y., Park, J., & Koltun, V. (2016). Fast global registration. In Proceedings of European conference on computer vision (ECCV).","DOI":"10.1007\/978-3-319-46475-6_47"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01709-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-022-01709-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01709-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T07:01:39Z","timestamp":1676617299000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-022-01709-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,14]]},"references-count":90,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["1709"],"URL":"https:\/\/doi.org\/10.1007\/s11263-022-01709-2","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,14]]},"assertion":[{"value":"2 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 December 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}