Abstract:In this paper, we study the asymptotic properties of regularized least squares with indefinite kernels in reproducing kernel Kreȋn spaces (RKKS). By introducing a bounded hyper-sphere constraint to such non-convex regularized risk minimization problem, we theoretically demonstrate that this problem has a globally optimal solution with a closed form on the sphere, which makes approximation analysis feasible in RKKS. Regarding to the original regularizer induced by the indefinite inner product, we modify traditi… Show more
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