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Inexact High-Order Proximal-Point Methods with Auxiliary Search Procedure
In this paper, we complement the framework of bilevel unconstrained minimization (BLUM) [Y. Nesterov, Math. Program., to appear] by a new pth-order proximal-point method convergent as O(k−(3p+1)/2), where k is the iteration counter. As compared with [Y. Nesterov, Math. Program., to appear], we replace the auxiliary line search by a segment search. This allows us to bound its complexity by a logarithm of the desired accuracy. Each step in this search needs an approximate computation of a high-order proximal-point operator. Under the assumption on boundedness of (p+1)th derivative of the objective function, this can be done by one step of the pth-order augmented tensor method. In this way, for p=2, we get a new second-order method with the rate of convergence O(k−7/2) and logarithmic complexity of the auxiliary search at each iteration. Another possibility is to compute the proximal-point operator by lower-order minimization methods. As an example, for p=3, we consider the upper-level process convergent as O(k−5). Assuming the boundedness of fourth derivative, an appropriate approximation of the proximal-point operator can be computed by a second-order method in logarithmic number of iterations. This combination gives a second-order scheme with much better complexity than the existing theoretical limits.
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