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We suggest simple implementable modifications of conditional gradient andgradient projection methods for smooth convex optimization problems in Hilbertspaces. Usually, the custom methods attain only weak convergence. We provestrong convergence of the new versions and establish their complexityestimates, which appear similar to the convergence rate of the weaklyconvergent versions.

Gradient Methods with Regularization for Constrained Optimization Problems and Their Complexity Estimates