@Article{Waki:2008:ASS,
  author =       "Hayato Waki and Sunyoung Kim and Masakazu Kojima and Mazakazu Muramatsu",
  title =        "Algorithm 883: {SparsePOP} : a Sparse Semidefinite Programming Relaxation of Polynomial Optimization
                 Problems",
  journal =      "{ACM} Transactions on Mathematical Software",
  volume =       "35",
  number =       "2",
  month =        jul,
  year =         "2008",
  pages =        "15:1--15:13",
  URL =          "http://doi.acm.org/10.1145/1377612.1377619",
  abstract =     "SparesPOP is a MATLAB implementation of the sparse semidefinite programming (SDP) relaxation method 
                 for approximating a global optimal solution of a polynomial optimization problem (POP) proposed by Waki, 
                 Kim, Kojima and Muramatsu. The sparse SDP relaxation exploits a sparse structure of polynomials in POPs
                 when applying ``a hierarchy of LMI relaxations of increasing dimensions'' by Lasserre. The efficiency of 
                 SparsePOP to approximate optimal solutions of POPs is thus increased, and larger scale POPs can be handled.",
}