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Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming
In this paper, we show that a large class of kernel learning problems can be reformulated as semidefinite-quadratic-linear programs (SQLPs), which only contain a simple positive semidefinite constraint, a second-order cone constraint and a number of linear constraints.
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