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math.OC2019
Error bound conditions and convergence of optimization methods on smooth and proximally smooth manifolds
Maxim Balashov, Andrey Tremba
We analyse the convergence of the gradient projection algorithm, which is finalized with the Newton method, to a stationary point for the problem of nonconvex constrained optimizat…
math.OC2019
Gradient projection and conditional gradient methods for constrained nonconvex minimization
Maxim Balashov, Boris Polyak, Andrey Tremba
Minimization of a smooth function on a sphere or, more generally, on a smooth manifold, is the simplest non-convex optimization problem. It has a lot of applications. Our goal is t…