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Adaptive cubic regularisation methods for unconstrained optimization. Part II: Worst-case function-and derivative-evaluation complexity
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C. Cartis, N. I. M. Gould, and Ph. L. Toint, Adaptive cubic regularisation methods for unconstrained optimization. Part II: Worst-case function-and derivative-evaluation complexity, Math. Program., 130 (2011), pp. 295-319.
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An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity
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C. Cartis, N. I. M. Gould, and Ph. L. Toint, An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity, IMA J. Numer. Anal., to appear.
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IMA J. Numer. Anal.
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On the complexity of steepest descent, Newton's and regularized Newton's methods for nonconvex unconstrained optimization
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A. R. Conn, N. I. M. Gould, and Ph. L. Toint, Trust-Region Methods, SIAM, Philadelphia, 2000.
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Trust-Region Methods
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Nonlinear programming without a penalty function or a filter
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