dual of rank constrained SDPs












0














The standard rank constrained SDP is as follows:
$$
min , Tr(CX),\ text{ s.t } Tr(A_iX)= b_i text{ for } i = 1,2,...,m ,,\ X >= 0,\ Rank(X) <= r
$$



I was interested in a lower bounding a particular rank constrained SDP. I was trying out the following : 1) Formulate above using the non-linear formulation of Burer-Monteiro . 2) Find a dual feasible solution and report obj value.



The non-linear version of the above would be



$$
min , Tr(CVV^T),\ text{ s.t } Tr(A_iVV^T)= b_i text{ for } i = 1,2,...,m \V in mathbb{R}^{n times r}.
$$



However, taking the Lagrangian Dual of this doesn't seem to be fruitful, at least for my SDP of interest.



Is there another way out? If not analytically, but say numerically ? When I use a nonlinear solver like 'fmincon' on MATLAB, I end up getting a large duality gap and a bad lower bound.










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  • The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
    – LinAlg
    Jan 4 at 14:53
















0














The standard rank constrained SDP is as follows:
$$
min , Tr(CX),\ text{ s.t } Tr(A_iX)= b_i text{ for } i = 1,2,...,m ,,\ X >= 0,\ Rank(X) <= r
$$



I was interested in a lower bounding a particular rank constrained SDP. I was trying out the following : 1) Formulate above using the non-linear formulation of Burer-Monteiro . 2) Find a dual feasible solution and report obj value.



The non-linear version of the above would be



$$
min , Tr(CVV^T),\ text{ s.t } Tr(A_iVV^T)= b_i text{ for } i = 1,2,...,m \V in mathbb{R}^{n times r}.
$$



However, taking the Lagrangian Dual of this doesn't seem to be fruitful, at least for my SDP of interest.



Is there another way out? If not analytically, but say numerically ? When I use a nonlinear solver like 'fmincon' on MATLAB, I end up getting a large duality gap and a bad lower bound.










share|cite|improve this question







New contributor




Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.




















  • The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
    – LinAlg
    Jan 4 at 14:53














0












0








0







The standard rank constrained SDP is as follows:
$$
min , Tr(CX),\ text{ s.t } Tr(A_iX)= b_i text{ for } i = 1,2,...,m ,,\ X >= 0,\ Rank(X) <= r
$$



I was interested in a lower bounding a particular rank constrained SDP. I was trying out the following : 1) Formulate above using the non-linear formulation of Burer-Monteiro . 2) Find a dual feasible solution and report obj value.



The non-linear version of the above would be



$$
min , Tr(CVV^T),\ text{ s.t } Tr(A_iVV^T)= b_i text{ for } i = 1,2,...,m \V in mathbb{R}^{n times r}.
$$



However, taking the Lagrangian Dual of this doesn't seem to be fruitful, at least for my SDP of interest.



Is there another way out? If not analytically, but say numerically ? When I use a nonlinear solver like 'fmincon' on MATLAB, I end up getting a large duality gap and a bad lower bound.










share|cite|improve this question







New contributor




Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











The standard rank constrained SDP is as follows:
$$
min , Tr(CX),\ text{ s.t } Tr(A_iX)= b_i text{ for } i = 1,2,...,m ,,\ X >= 0,\ Rank(X) <= r
$$



I was interested in a lower bounding a particular rank constrained SDP. I was trying out the following : 1) Formulate above using the non-linear formulation of Burer-Monteiro . 2) Find a dual feasible solution and report obj value.



The non-linear version of the above would be



$$
min , Tr(CVV^T),\ text{ s.t } Tr(A_iVV^T)= b_i text{ for } i = 1,2,...,m \V in mathbb{R}^{n times r}.
$$



However, taking the Lagrangian Dual of this doesn't seem to be fruitful, at least for my SDP of interest.



Is there another way out? If not analytically, but say numerically ? When I use a nonlinear solver like 'fmincon' on MATLAB, I end up getting a large duality gap and a bad lower bound.







optimization nonlinear-optimization duality-theorems semidefinite-programming






share|cite|improve this question







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Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|cite|improve this question







New contributor




Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|cite|improve this question




share|cite|improve this question






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Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked Jan 4 at 12:15









Maharshi RayMaharshi Ray

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New contributor





Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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Maharshi Ray is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.












  • The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
    – LinAlg
    Jan 4 at 14:53


















  • The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
    – LinAlg
    Jan 4 at 14:53
















The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
– LinAlg
Jan 4 at 14:53




The paper by Burer and Monteiro has some leads on solving the nonlinear version. Can you show the dual formulation that you derived?
– LinAlg
Jan 4 at 14:53










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