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An Efficient Semismooth Newton Based Algorithm for Convex Clustering.

, , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5704-5712. PMLR, (2018)

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Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm., , and . CoRR, (2018)Spectral operators of matrices., , , and . Math. Program., 168 (1-2): 509-531 (2018)An Efficient Semismooth Newton Based Algorithm for Convex Clustering., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5704-5712. PMLR, (2018)Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian., , , and . SIAM J. Optimization, 30 (1): 630-659 (2020)A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization., , and . SIAM J. Optimization, 26 (2): 922-950 (2016)A Squared Smoothing Newton Method for Nonsmooth Matrix Equations and Its Applications in Semidefinite Optimization Problems., , and . SIAM J. Optimization, 14 (3): 783-806 (2004)A New Unconstrained Differentiable Merit Function for Box Constrained Variational Inequality Problems and a Damped Gauss-Newton Method., and . SIAM J. Optimization, 9 (2): 388-413 (1999)On NCP-Functions., and . Comput. Optim. Appl., 13 (1-3): 201-220 (1999)An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems., , , and . Math. Program., 179 (1): 223-263 (2020)On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models., , , and . CoRR, (2019)