Approximation in the Wasserstein distance with application to clustering

[1]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[2]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[3]  J. Vitter,et al.  Approximations with Minimum Packing Constraint Violation , 1992 .

[4]  Vijay V. Vazirani,et al.  Approximation algorithms for metric facility location and k-Median problems using the primal-dual schema and Lagrangian relaxation , 2001, JACM.

[5]  Michael Elad,et al.  From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..

[6]  Stephen P. Boyd,et al.  A rank minimization heuristic with application to minimum order system approximation , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[7]  Sudipto Guha,et al.  A constant-factor approximation algorithm for the k-median problem (extended abstract) , 1999, STOC '99.

[8]  Mark S. Daskin,et al.  Network and Discrete Location: Models, Algorithms and Applications , 1995 .

[9]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[10]  Venkat Chandrasekaran,et al.  Recovery of Sparse Probability Measures via Convex Programming , 2012, NIPS.

[11]  Emmanuel J. Candès,et al.  Decoding by linear programming , 2005, IEEE Transactions on Information Theory.

[12]  M. Yuan,et al.  Model selection and estimation in regression with grouped variables , 2006 .

[13]  Zvi Drezner,et al.  Facility location - applications and theory , 2001 .

[14]  A. Willsky,et al.  The Convex algebraic geometry of linear inverse problems , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).