Sparse Approximate Solutions to Semidefinite Programs

  • Elad Hazan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4957)


We propose an algorithm for approximately maximizing a concave function over the bounded semi-definite cone, which produces sparse solutions. Sparsity for SDP corresponds to low rank matrices, and is a important property for both computational as well as learning theoretic reasons. As an application, building on Aaronson’s recent work, we derive a linear time algorithm for Quantum State Tomography.


Curvature Constant Interior Point Method Linear Time Algorithm Sparse Solution Lanczos Algorithm 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Elad Hazan
    • 1
  1. 1.IBM Almaden Research CenterSan JoseUSA

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