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Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization

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  1. Paul Tseng, 2004. "An Analysis of the EM Algorithm and Entropy-Like Proximal Point Methods," Mathematics of Operations Research, INFORMS, vol. 29(1), pages 27-44, February.
  2. Omer, E. & Guetta, R. & Ioslovich, I. & Gutman, P.O. & Borshchevsky, M., 2008. "“Energy Tower” combined with pumped storage and desalination: Optimal design and analysis," Renewable Energy, Elsevier, vol. 33(4), pages 597-607.
  3. Sarah Perrin & Thierry Roncalli, 2019. "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers 1909.10233, arXiv.org.
  4. Bottmer, Lea & Croux, Christophe & Wilms, Ines, 2022. "Sparse regression for large data sets with outliers," European Journal of Operational Research, Elsevier, vol. 297(2), pages 782-794.
  5. James C. Spall, 2012. "Cyclic Seesaw Process for Optimization and Identification," Journal of Optimization Theory and Applications, Springer, vol. 154(1), pages 187-208, July.
  6. Jun Yan & Jian Huang, 2012. "Model Selection for Cox Models with Time-Varying Coefficients," Biometrics, The International Biometric Society, vol. 68(2), pages 419-428, June.
  7. Bak, Kwan-Young & Jhong, Jae-Hwan & Lee, JungJun & Shin, Jae-Kyung & Koo, Ja-Yong, 2021. "Penalized logspline density estimation using total variation penalty," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  8. Vincent, Martin & Hansen, Niels Richard, 2014. "Sparse group lasso and high dimensional multinomial classification," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 771-786.
  9. Evans, R.J. & Forcina, A., 2013. "Two algorithms for fitting constrained marginal models," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 1-7.
  10. Young-Geun Choi & Seunghwan Lee & Donghyeon Yu, 2022. "An efficient parallel block coordinate descent algorithm for large-scale precision matrix estimation using graphics processing units," Computational Statistics, Springer, vol. 37(1), pages 419-443, March.
  11. Baiguo An & Beibei Zhang, 2020. "Logistic regression with image covariates via the combination of L1 and Sobolev regularizations," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-18, June.
  12. Shuang Zhang & Xingdong Feng, 2022. "Distributed identification of heterogeneous treatment effects," Computational Statistics, Springer, vol. 37(1), pages 57-89, March.
  13. Dewei Zhang & Yin Liu & Sam Davanloo Tajbakhsh, 2022. "A First-Order Optimization Algorithm for Statistical Learning with Hierarchical Sparsity Structure," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1126-1140, March.
  14. Jung, Yoon Mo & Whang, Joyce Jiyoung & Yun, Sangwoon, 2020. "Sparse probabilistic K-means," Applied Mathematics and Computation, Elsevier, vol. 382(C).
  15. Rok Hribar & Timotej Hrga & Gregor Papa & Gašper Petelin & Janez Povh & Nataša Pržulj & Vida Vukašinović, 2022. "Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem," Journal of Global Optimization, Springer, vol. 82(2), pages 283-312, February.
  16. Petra Posedel v{S}imovi'c & Davor Horvatic & Edward W. Sun, 2021. "Classifying variety of customer's online engagement for churn prediction with mixed-penalty logistic regression," Papers 2105.07671, arXiv.org, revised Jul 2021.
  17. Justin A. Sirignano & Gerry Tsoukalas & Kay Giesecke, 2016. "Large-Scale Loan Portfolio Selection," Operations Research, INFORMS, vol. 64(6), pages 1239-1255, December.
  18. Yangyang Xu, 2019. "Asynchronous parallel primal–dual block coordinate update methods for affinely constrained convex programs," Computational Optimization and Applications, Springer, vol. 72(1), pages 87-113, January.
  19. Jin Liu & Jian Huang & Yawei Zhang & Qing Lan & Nathaniel Rothman & Tongzhang Zheng & Shuangge Ma, 2014. "Integrative analysis of prognosis data on multiple cancer subtypes," Biometrics, The International Biometric Society, vol. 70(3), pages 480-488, September.
  20. Petra P. Šimović & Claire Y. T. Chen & Edward W. Sun, 2023. "Classifying the Variety of Customers’ Online Engagement for Churn Prediction with a Mixed-Penalty Logistic Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 451-485, January.
  21. Kimon Fountoulakis & Jacek Gondzio, 2016. "Performance of first- and second-order methods for $$\ell _1$$ ℓ 1 -regularized least squares problems," Computational Optimization and Applications, Springer, vol. 65(3), pages 605-635, December.
  22. Davood Hajinezhad & Qingjiang Shi, 2018. "Alternating direction method of multipliers for a class of nonconvex bilinear optimization: convergence analysis and applications," Journal of Global Optimization, Springer, vol. 70(1), pages 261-288, January.
  23. Emilie Devijver, 2017. "Model-based regression clustering for high-dimensional data: application to functional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 243-279, June.
  24. Masoud Ahookhosh & Le Thi Khanh Hien & Nicolas Gillis & Panagiotis Patrinos, 2021. "Multi-block Bregman proximal alternating linearized minimization and its application to orthogonal nonnegative matrix factorization," Computational Optimization and Applications, Springer, vol. 79(3), pages 681-715, July.
  25. Mingyi Hong & Tsung-Hui Chang & Xiangfeng Wang & Meisam Razaviyayn & Shiqian Ma & Zhi-Quan Luo, 2020. "A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 833-861, August.
  26. Xiangguang Dai & Chuandong Li & Biqun Xiang, 2018. "Graph Sparse Nonnegative Matrix Factorization Algorithm Based on the Inertial Projection Neural Network," Complexity, Hindawi, vol. 2018, pages 1-12, March.
  27. X. Wang & S. Li & X. Kou & Q. Zhang, 2015. "A new alternating direction method for linearly constrained nonconvex optimization problems," Journal of Global Optimization, Springer, vol. 62(4), pages 695-709, August.
  28. Seunghwan Lee & Sang Cheol Kim & Donghyeon Yu, 2023. "An efficient GPU-parallel coordinate descent algorithm for sparse precision matrix estimation via scaled lasso," Computational Statistics, Springer, vol. 38(1), pages 217-242, March.
  29. Yen, Yu-Min & Yen, Tso-Jung, 2014. "Solving norm constrained portfolio optimization via coordinate-wise descent algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 737-759.
  30. Cheik Traoré & Saverio Salzo & Silvia Villa, 2023. "Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization," Computational Optimization and Applications, Springer, vol. 86(1), pages 303-344, September.
  31. Le Thi Khanh Hien & Duy Nhat Phan & Nicolas Gillis, 2022. "Inertial alternating direction method of multipliers for non-convex non-smooth optimization," Computational Optimization and Applications, Springer, vol. 83(1), pages 247-285, September.
  32. Yudong Wang & Zhi‐Sheng Ye & Hongyuan Cao, 2021. "On computation of semiparametric maximum likelihood estimators with shape constraints," Biometrics, The International Biometric Society, vol. 77(1), pages 113-124, March.
  33. Zhigeng Geng & Sijian Wang & Menggang Yu & Patrick O. Monahan & Victoria Champion & Grace Wahba, 2015. "Group variable selection via convex log-exp-sum penalty with application to a breast cancer survivor study," Biometrics, The International Biometric Society, vol. 71(1), pages 53-62, March.
  34. Ye, Gui-Bo & Xie, Xiaohui, 2011. "Split Bregman method for large scale fused Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1552-1569, April.
  35. Cristofari, Andrea, 2023. "A decomposition method for lasso problems with zero-sum constraint," European Journal of Operational Research, Elsevier, vol. 306(1), pages 358-369.
  36. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
  37. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
  38. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
  39. Alexander Murray & Timm Faulwasser & Veit Hagenmeyer & Mario E. Villanueva & Boris Houska, 2021. "Partially distributed outer approximation," Journal of Global Optimization, Springer, vol. 80(3), pages 523-550, July.
  40. Brian Dandurand & Margaret M. Wiecek, 2016. "Quadratic scalarization for decomposed multiobjective optimization," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(4), pages 1071-1096, October.
  41. Gaynanova, Irina & Wang, Tianying, 2019. "Sparse quadratic classification rules via linear dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 278-299.
  42. Liron Ravner & Yoni Nazarathy, 2017. "Scheduling for a processor sharing system with linear slowdown," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(1), pages 71-102, August.
  43. Emilie Chouzenoux & Jean-Christophe Pesquet & Audrey Repetti, 2016. "A block coordinate variable metric forward–backward algorithm," Journal of Global Optimization, Springer, vol. 66(3), pages 457-485, November.
  44. Michoel, Tom, 2016. "Natural coordinate descent algorithm for L1-penalised regression in generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 60-70.
  45. Garcia-Magariños Manuel & Antoniadis Anestis & Cao Ricardo & González-Manteiga Wenceslao, 2010. "Lasso Logistic Regression, GSoft and the Cyclic Coordinate Descent Algorithm: Application to Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-30, August.
  46. Christoph Buchheim & Marcia Fampa & Orlando Sarmiento, 2021. "Lower Bounds for Cubic Optimization over the Sphere," Journal of Optimization Theory and Applications, Springer, vol. 188(3), pages 823-846, March.
  47. Enrico Civitelli & Matteo Lapucci & Fabio Schoen & Alessio Sortino, 2021. "An effective procedure for feature subset selection in logistic regression based on information criteria," Computational Optimization and Applications, Springer, vol. 80(1), pages 1-32, September.
  48. Manlio Gaudioso & Giovanni Giallombardo & Giovanna Miglionico, 2015. "Optimal Replenishment Order Placement in a Finite Time Horizon," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 1078-1089, March.
  49. Sven Jäger & Anita Schöbel, 2020. "The blockwise coordinate descent method for integer programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 91(2), pages 357-381, April.
  50. Lukas Meier & Sara Van De Geer & Peter Bühlmann, 2008. "The group lasso for logistic regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 53-71, February.
  51. David Degras, 2021. "Sparse group fused lasso for model segmentation: a hybrid approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 625-671, September.
  52. Masoud Ahookhosh & Le Thi Khanh Hien & Nicolas Gillis & Panagiotis Patrinos, 2021. "A Block Inertial Bregman Proximal Algorithm for Nonsmooth Nonconvex Problems with Application to Symmetric Nonnegative Matrix Tri-Factorization," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 234-258, July.
  53. Astorino, Annabella & Avolio, Matteo & Fuduli, Antonio, 2022. "A maximum-margin multisphere approach for binary Multiple Instance Learning," European Journal of Operational Research, Elsevier, vol. 299(2), pages 642-652.
  54. Nurudeen A. Adegoke & Andrew Punnett & Marti J. Anderson, 2022. "Estimation of Multivariate Dependence Structures via Constrained Maximum Likelihood," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 240-260, June.
  55. Jacob Bien & Florentina Bunea & Luo Xiao, 2016. "Convex Banding of the Covariance Matrix," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 834-845, April.
  56. Matthew Pietrosanu & Jueyu Gao & Linglong Kong & Bei Jiang & Di Niu, 2021. "Advanced algorithms for penalized quantile and composite quantile regression," Computational Statistics, Springer, vol. 36(1), pages 333-346, March.
  57. Griveau-Billion, Théophile & Richard, Jean-Charles & Roncalli, Thierry, 2013. "A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios," MPRA Paper 49822, University Library of Munich, Germany.
  58. Hédy Attouch & Jérôme Bolte & Patrick Redont & Antoine Soubeyran, 2010. "Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality," Mathematics of Operations Research, INFORMS, vol. 35(2), pages 438-457, May.
  59. Sung, Bongjung & Lee, Jaeyong, 2023. "Covariance structure estimation with Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  60. Jian Zhang, 2010. "A Bayesian model for biclustering with applications," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(4), pages 635-656, August.
  61. Rui Yao & Shlomo Bekhor, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Papers 2303.16595, arXiv.org, revised Dec 2023.
  62. Jin Liu & Shuangge Ma & Jian Huang, 2014. "Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 87-103, March.
  63. Ron Shefi & Marc Teboulle, 2016. "On the rate of convergence of the proximal alternating linearized minimization algorithm for convex problems," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(1), pages 27-46, February.
  64. Sylvain Sardy & Paul Tseng, 2010. "Density Estimation by Total Variation Penalized Likelihood Driven by the Sparsity ℓ1 Information Criterion," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 321-337, June.
  65. Mingrui Zhong & Zanhua Yin & Zhichao Wang, 2023. "Variable Selection for Sparse Logistic Regression with Grouped Variables," Mathematics, MDPI, vol. 11(24), pages 1-21, December.
  66. Jinlong Lei & Uday V. Shanbhag, 2020. "Asynchronous Schemes for Stochastic and Misspecified Potential Games and Nonconvex Optimization," Operations Research, INFORMS, vol. 68(6), pages 1742-1766, November.
  67. Chen, Zhen-Yu & Fan, Zhi-Ping & Sun, Minghe, 2012. "A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data," European Journal of Operational Research, Elsevier, vol. 223(2), pages 461-472.
  68. Rosember Guerra-Urzola & Niek C. Schipper & Anya Tonne & Klaas Sijtsma & Juan C. Vera & Katrijn Deun, 2023. "Sparsifying the least-squares approach to PCA: comparison of lasso and cardinality constraint," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 269-286, March.
  69. Benjamin G. Stokell & Rajen D. Shah & Ryan J. Tibshirani, 2021. "Modelling high‐dimensional categorical data using nonconvex fusion penalties," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 579-611, July.
  70. Yunzhang Zhu & Xiaotong Shen & Wei Pan, 2014. "Structural Pursuit Over Multiple Undirected Graphs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1683-1696, December.
  71. Ruoyu Sun & Zhi-Quan Luo & Yinyu Ye, 2020. "On the Efficiency of Random Permutation for ADMM and Coordinate Descent," Mathematics of Operations Research, INFORMS, vol. 45(1), pages 233-271, February.
  72. He, Shiyuan & Yin, Jianxin & Li, Hongzhe & Wang, Xing, 2014. "Graphical model selection and estimation for high dimensional tensor data," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 165-185.
  73. Wu, Cen & Zhang, Qingzhao & Jiang, Yu & Ma, Shuangge, 2018. "Robust network-based analysis of the associations between (epi)genetic measurements," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 119-130.
  74. Fang, Kuangnan & Wang, Xiaoyan & Shia, Ben-Chang & Ma, Shuangge, 2016. "Identification of proportionality structure with two-part models using penalization," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 12-24.
  75. Fang, Kuangnan & Chen, Yuanxing & Ma, Shuangge & Zhang, Qingzhao, 2022. "Biclustering analysis of functionals via penalized fusion," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  76. Haibin Chen & Hongjin He & Yiju Wang & Guanglu Zhou, 2022. "An efficient alternating minimization method for fourth degree polynomial optimization," Journal of Global Optimization, Springer, vol. 82(1), pages 83-103, January.
  77. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.
  78. Pan, Yuqing & Mai, Qing, 2020. "Efficient computation for differential network analysis with applications to quadratic discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  79. Fang, Qian & Yu, Chen & Weiping, Zhang, 2020. "Regularized estimation of precision matrix for high-dimensional multivariate longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
  80. Dvijotham, Krishnamurthy & Rabani, Yuval & Schulman, Leonard J., 2022. "Convergence of incentive-driven dynamics in Fisher markets," Games and Economic Behavior, Elsevier, vol. 134(C), pages 361-375.
  81. Rachael Tappenden & Peter Richtárik & Jacek Gondzio, 2016. "Inexact Coordinate Descent: Complexity and Preconditioning," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 144-176, July.
  82. Z. John Daye & Jinbo Chen & Hongzhe Li, 2012. "High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis," Biometrics, The International Biometric Society, vol. 68(1), pages 316-326, March.
  83. Wu, Tong Tong & He, Xin, 2012. "Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 25-33, January.
  84. Yunfeng Zhang & Irina Gaynanova, 2022. "Joint association and classification analysis of multi‐view data," Biometrics, The International Biometric Society, vol. 78(4), pages 1614-1625, December.
  85. Fan, Xinyan & Zhang, Qingzhao & Ma, Shuangge & Fang, Kuangnan, 2021. "Conditional score matching for high-dimensional partial graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  86. Yanming Li & Bin Nan & Ji Zhu, 2015. "Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure," Biometrics, The International Biometric Society, vol. 71(2), pages 354-363, June.
  87. Chen, Kun & Huang, Rui & Chan, Ngai Hang & Yau, Chun Yip, 2019. "Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 8-18.
  88. Zhigang Li & Mingchuan Zhang & Junlong Zhu & Ruijuan Zheng & Qikun Zhang & Qingtao Wu, 2018. "Stochastic Block-Coordinate Gradient Projection Algorithms for Submodular Maximization," Complexity, Hindawi, vol. 2018, pages 1-11, December.
  89. Yuning Yang, 2023. "On global convergence of alternating least squares for tensor approximation," Computational Optimization and Applications, Springer, vol. 84(2), pages 509-529, March.
  90. Lei Yang & Zheng-Hai Huang & Shenglong Hu & Jiye Han, 2016. "An iterative algorithm for third-order tensor multi-rank minimization," Computational Optimization and Applications, Springer, vol. 63(1), pages 169-202, January.
  91. P. Tseng & S. Yun, 2009. "Block-Coordinate Gradient Descent Method for Linearly Constrained Nonsmooth Separable Optimization," Journal of Optimization Theory and Applications, Springer, vol. 140(3), pages 513-535, March.
  92. Kaida Cai & Hua Shen & Xuewen Lu, 2022. "Adaptive bi-level variable selection for multivariate failure time model with a diverging number of covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 968-993, December.
  93. Jean-Charles Richard & Thierry Roncalli, 2019. "Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles," Papers 1902.05710, arXiv.org.
  94. Michael R. Wierzbicki & Li-Bing Guo & Qing-Tao Du & Wensheng Guo, 2014. "Sparse Semiparametric Nonlinear Model With Application to Chromatographic Fingerprints," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1339-1349, December.
  95. Murat Genç, 2022. "A new double-regularized regression using Liu and lasso regularization," Computational Statistics, Springer, vol. 37(1), pages 159-227, March.
  96. Zhang, Jian & Gong, Weijie & Yue, Xinxin & Shi, Maolin & Chen, Lei, 2022. "Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
  97. Yao, Rui & Bekhor, Shlomo, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
  98. Runmin Shi & Faming Liang & Qifan Song & Ye Luo & Malay Ghosh, 2018. "A Blockwise Consistency Method for Parameter Estimation of Complex Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 179-223, December.
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