4 papers
Adaptive Regularized Newton Method with Inexact Hessian
Aleksandr Shestakov, Nail Bashirov, Andrei Semenov +4
Newton's method is the most widespread high-order method, demanding the gradient and the Hessian of the objective function. However, one of the main disadvantages of Newtons method…
A Damped Newton Method Achieves Global and Local Quadratic Convergence Rate
Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk +3
In this paper, we present the first stepsize schedule for Newton method resulting in fast global and local convergence guarantees. In particular, a) we prove an $O\left( \frac 1 {k…
Accelerated meta-algorithm for convex optimization
Alexander Gasnikov, Darina Dvinskikh, Pavel Dvurechensky +5
We propose an accelerated meta-algorithm, which allows to obtain accelerated methods for convex unconstrained minimization in different settings. As an application of the general s…
On the Optimal Combination of Tensor Optimization Methods
Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky
We consider the minimization problem of a sum of a number of functions having Lipshitz -th order derivatives with different Lipschitz constants. In this case, to accelerate opti…