»ã±¨±êÌâ (Title)£ºCyclic gradient methods for unconstrained optimization£¨ÎÞÔ¼ÊøÓÅ»¯ÎÊÌâµÄÑ­»·Ìݶȷ¨£©

»ã±¨ÈË (Speaker)£º Ëï´Ï ¸±½ÌÊÚ£¨±±¾©Óʵç´óѧ£©

»ã±¨¹¦·ò (Time)£º2022Äê12ÔÂ13ÈÕ(Öܶþ) 10:00-11:00

»ã±¨µØÖ· (Place)£ºÌÚѶ»áÒé (»áÒéºÅ£º225-921-874)

Ô¼ÇëÈË(Inviter)£ºÐì×Ë

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»ã±¨ÌáÒª£ºIn this work, the cyclic gradient method with Cauchy steps and constructed constant steps for convex quadratic function minimization problems are extended to general smooth unconstrained optimization problems. The Cauchy steps are approximated first by the step-ahead BB steps, and then by the interpolation. The convergence properties of the proposed methods are analyzed. Numerical results show the good performances of the proposed gradient methods compared to the benchmarks.