[1] Ansorge, R.: Connections between the Cimmino-method and the Kaczmarz-method for the solution of singular and regular systems of equations. Computing 33(3), 367-375 (1984)
[2] Bai, Z.-Z., Jin, C.-H.: Column-decomposed relaxation methods for the overdetermined systems of linear equations. Int. J. Appl. Math. 13(1), 71-82 (2003)
[3] Bai, Z.-Z., Liu, X.-G.: On the Meany inequality with applications to convergence analysis of several row-action iteration methods. Numer. Math. 124(2), 215-236 (2013)
[4] Bai, Z.-Z., RozloznÍk, M.: On the numerical behavior of matrix splitting iteration methods for solving linear systems. SIAM J. Numer. Anal. 53(4), 1716-1737 (2015)
[5] Bai, Z.-Z., Wang, L.: On multi-step randomized extended Kaczmarz method for solving large sparse inconsistent linear systems. Appl. Numer. Math. 192, 197-213 (2023)
[6] Bai, Z.-Z., Wang, L.: On convergence rates of Kaczmarz-type methods with different selection rules of working rows. Appl. Numer. Math. 186, 289-319 (2023)
[7] Bai, Z.-Z., Wu, W.-T.: On greedy randomized Kaczmarz method for solving large sparse linear systems. SIAM J. Sci. Comput. 40(1), A592-A606 (2018)
[8] Bai, Z.-Z., Wu, W.-T.: On relaxed greedy randomized Kaczmarz methods for solving large sparse linear systems. Appl. Math. Lett. 83, 21-26 (2018)
[9] Bai, Z.-Z., Wu, W.-T.: On convergence rate of the randomized Kaczmarz method. Linear Algebra Appl. 553, 252-269 (2018)
[10] Bai, Z.-Z., Wu, W.-T.: On partially randomized extended Kaczmarz method for solving large sparse overdetermined inconsistent linear systems. Linear Algebra Appl. 578, 225-250 (2019)
[11] Bai, Z.-Z., Wu, W.-T.: On greedy randomized coordinate descent methods for solving large linear least-squares problems. Numer. Linear Algebra Appl. 26(4), 1-15 (2019)
[12] Bai, Z.-Z., Wu, W.-T.: Randomized Kaczmarz iteration methods: algorithmic extensions and convergence theory. Jpn. J. Ind. Appl. Math. 40, 1-23 (2023)
[13] Brezinski, C.: Projection Methods for Systems of Equations. Elsevier Science, Amsterdam (1997)
[14] Byrne, C.: A unified treatment of some iterative algorithms in signal processing and image reconstruction. Inverse Probl. 20(1), 103-120 (2003)
[15] Byrne, C.L.: Applied Iterative Methods. A.K. Peters, Wellesley (2007)
[16] Censor, Y.: Row-action methods for huge and sparse systems and their applications. SIAM Rev. 23(4), 444-466 (1981)
[17] Censor, Y.: Parallel application of block-iterative methods in medical imaging and radiation therapy. Math. Program. 42(1), 307-325 (1988)
[18] Davis, T.A., Hu, Y.: The University of Florida sparse matrix collection. ACM Trans. Math. Softw. 38, 1-25 (2011)
[19] Du, K., Gao, H.: A new theoretical estimate for the convergence rate of the maximal weighted residual Kaczmarz algorithm. Numer. Math. Theory Methods Appl. 12(2), 627-639 (2019)
[20] Eggermont, P.P.B., Herman, G.T., Lent, A.: Iterative algorithms for large partitioned linear systems, with applications to image reconstruction. Linear Algebra Appl. 40, 37-67 (1981)
[21] Elble, J.M., Sahinidis, N.V., Vouzis, P.: GPU computing with Kaczmarz’s and other iterative algorithms for linear systems. Parallel Comput. 36, 215-231 (2010)
[22] Galántai, A.: Projectors and Projection Methods. Kluwer Academic Publishers, Norwell (2004)
[23] Gower, R.M., Richtárik, P.: Stochastic dual ascent for solving linear systems. https://arxiv.org/abs/1512.06890 (2015)
[24] Herman, G.T., Davidi, R.: Image reconstruction from a small number of projections. Inverse Probl. 24(4), 1-18 (2008)
[25] Herman, G.T., Meyer, L.B.: Algebraic reconstruction techniques can be made computationally efficient (positron emission tomography application). IEEE Trans. Med. Imaging 12, 600-609 (1993)
[26] Kaczmarz, S.: Angenäherte Auflösung von Systemen linearer Gleichungen. Bull. Int. Acad. Polon. Sci. Lett. A 35, 355-357 (1937)
[27] Knight, P.A.: Error Analysis of Stationary Iteration and Associated Problems. Ph. D. thesis, Manchester University, Manchester (1993)
[28] Leventhal, D., Lewis, A.S.: Randomized methods for linear constraints: convergence rates and conditioning. Math. Oper. Res. 35, 641-654 (2010)
[29] Lorenz, D.A., Wenger, S., Schöpfer, F., Magnor, M.: A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing. In: 2014 IEEE International Conference on Image Processing (ICIP), Paris, France, 1347-1351 (2014)
[30] Ma, A., Needell, D., Ramdas, A.: Convergence properties of the randomized extended Gauss-Seidel and Kaczmarz methods. SIAM J. Matrix Anal. Appl. 36, 1590-1604 (2015)
[31] McCormick, S.F.: The methods of Kaczmarz and row orthogonalization for solving linear equations and least squares problems in Hilbert space. Indiana Univ. Math. J. 26, 1137-1150 (1977)
[32] Natterer, F.: The Mathematics of Computerized Tomography. SIAM, Philadelphia (2001)
[33] Needell, D.: Randomized Kaczmarz solver for noisy linear systems. BIT Numer. Math. 50, 395-403 (2010)
[34] Needell, D., Tropp, J.A.: Paved with good intentions: analysis of a randomized block Kaczmarz method. Linear Algebra Appl. 441, 199-221 (2014)
[35] Pasqualetti, F., Carli, R., Bullo, F.: Distributed estimation via iterative projections with application to power network monitoring. Automatica J. IFAC 48, 747-758 (2012)
[36] Popa, C., Zdunek, R.: Kaczmarz extended algorithm for tomographic image reconstruction from limited-data. Math. Comput. Simul. 65, 579-598 (2004)
[37] Strohmer, T., Vershynin, R.: A randomized Kaczmarz algorithm with exponential convergence. J. Fourier Anal. Appl. 15, 262-278 (2009)
[38] Tan, L.-Z., Guo, X.-P.: On multi-step greedy randomized coordinate descent method for solving large linear least-squares problems. Comput. Appl. Math. 42(37), 1-20 (2023)
[39] Zhang, J.-J.: A new greedy Kaczmarz algorithm for the solution of very large linear systems. Appl. Math. Lett. 91, 207-212 (2019)
[40] Zhang, J.-J., Guo, J.-H.: On relaxed greedy randomized coordinate descent methods for solving large linear least-squares problems. Appl. Numer. Math. 157, 372-384 (2020)
[41] Zhang, K., Li, F.-T., Jiang, X.-L.: Multi-step greedy Kaczmarz algorithms with simple random sampling for solving large linear systems. Comput. Appl. Math. 41(332), 1-25 (2022)
[42] Zouzias, A., Freris, N.M.: Randomized extended Kaczmarz for solving least squares. SIAM J. Matrix Anal. Appl. 34, 773-793 (2013)