Nuclear Norm and Matrix Recovery

• A. Ben-Tal and A. Nemirovski.
  "Solving large scale polynomial convex problems on \ell_1/nuclear norm balls by randomized first-order algorithms",
  Preprint, Faculty of Industrial Engineering and Management, Technion, October 2012.
  opt-online
• Z. Luo, J. Tao and N. Xiu.
  "Lowest-rank Solutions of Continuous and Discrete Lyapunov Equations over Symmetric Cone",
  Preprint, Department of Mathematics and Statistics, Loyola University Marylan, October 2012.
  opt-online
• G. Tang, B. N. Bhaskar, P. Shah and B. Recht.
  "Compressed Sensing Off the Grid",
  Preprint, University of Wisconsin Madison, September 2012.
  opt-online
• S. Bi and S. Pan.
  "Approximation of rank function and its application to the nearest low-rank correlation matrix",
  Department of Mathematics, South China University of Technology, Guangzhou City, China, July 10, 2011 .
  opt-online
• L. Kong, L. Tuncel and N. Xiu.
  "Sufficient Conditions for Low-rank Matrix Recovery, Translated from Sparse Signal Recovery",
  Reseach report, Department of Applied Mathematics, Beijing Jiaotong University, Beijing 100044, P.R. China, June 2011.
  opt-online
• B. Recht and C. Re.
  "Parallel Stochastic Gradient Algorithms for Large-Scale Matrix Completion",
  Computer Sciences Department, University of Wisconsin-Madison, April 2011.
  opt-online
• Y.-B. Zhao.
  "Approximation Theory of Matrix Rank Minimization and Its Application to Quadratic Equations",
  School of Mathematics, University of Birmingham, January 2011.
  opt-online
• V. Chandrasekaran, B. Recht, P. A. Parrilo, and Alan S. Willsky.
  "The Convex Geometry of Linear Inverse Problems",
  LIDS technical report 2857, Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, December 2010.
  opt-online
• X. V. Doan and S. A. Vavasis.
  "Finding approximately rank-one submatrices with the nuclear norm and l1 norm",
  Department of Combinatorics and Optimization, University of Waterloo, November 2010.
  opt-online
• S. Becker, E. Candés, and M, Grant.
  "Templates for Convex Cone Problems with Applications to Sparse Signal Recovery",
  Applied and Computational Mathematics, Caltech, September 2010.
  opt-online
• M. Jaggi and M. Sulovský.
  "A simple Algorithm for Nuclear Norm Regularized Problems",
  ICML 2010: Proceedings of the 27th International Conference on Machine Learning, Juni 2010.
  icml-paper
• Z. Wen, W. Yin and Y. Zhang.
  "Solving A Low-Rank Factorization Model for Matrix Completion by A Nonlinear Successive Over-Relaxation Algorithm",
  Technical Report TR10-07, Rice University, March 2010.
  opt-online
• J. Yang and X. Yuan.
  "An Inexact Alternating Direction Method for Trace Norm Regularized Least Squares Problem",
  Department of Mathematics, Nanjing University, February 2010.
  opt-online
• M. Tao and X. Yuan.
  "Recovering low-rank and sparse components of matrices from incomplete and noisy observations",
  Department of Mathematics, Nanjing University, December 2009.
  opt-online
• B. Recht.
  "A Simpler Approach to Matrix Completion",
  University of Wisconsin-Madison, October 2009.
  opt-online
• X. Yuan and J. Yang.
  "Sparse and Low-Rank Matrix Decomposition Via Alternating Direction Methods",
  Department of Mathematics, Hong Kong Baptist University, October 2009.
  opt-online
• X. Yuan.
  "Alternating Direction Methods for Sparse Covariance Selection",
  Department of Mathematics, Hong Kong Baptist University, September 2009.
  opt-online
• Y.-J. Liu, D. Sun and K.-C. Toh.
  "An Implementable Proximal Point Algorithmic Framework for Nuclear Norm Minimization",
  National University of Singapore, July, 2009.
  opt-online
• V. Chandrasekaran, S. Sanghavi, P. A. Parrilo and A. S. Willsky.
  "Rank-Sparsity Incoherence for Matrix Decomposition",
  Laboratory for Information and Decision Systems, Department of Electrical Enginneering and Computer Science, MIT, Cambridge, June 2009.
  opt-online
• D. Goldfarb and S. Ma.
  "Convergence of fixed point continuation algorithms for matrix rank minimization",
  Technical Report, Department of IEOR, Columbia University, June 2009.
  opt-online
• K.-C. Toh and S. Yun.
  "An accelerated proximal gradient algorithm for nuclear norm regularized least squares problems",
  Preprint, Department of Mathematics, National University of Singapore, March 2009.
  opt-online
• S. Ma, D. Goldfarb and L. Chen.
  "Fixed point and Bregman iterative methods for matrix rank minimization",
  Technical Report, Department of IEOR, Columbia University, October, 2008.
  opt-online
• B. Recht, M. Fazel and P. A. Parrilo.
  "Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization",
  Technical Report, Center for the Mathematics of Information, California Institute of Technology, 2007.
  opt-online