[ semidefinite programming ] - minimize the sum of k lowest eigenvalues ?

Hello,

I'd like to know how to formulate the minimization of f( Y ), f being
the sum of k lowest eigenvalues, Y a symmetric matrice, as a
semidefinite program.

I've found how to formulate the problem when f is the sum of k largest
eigenvalues in nesterov & nemirovskii's book ("interior-point
polynomial algorithms in convex programming), but i have not found a
way to minimize the sum of lowest eigenvalues. Any help would be nice

jef k.

.

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