500 citations · 1.2k across the 44 of their papers we have counts for
8 papers · 2 filters
Affine-invariant contracting-point methods for Convex Optimization
Nikita Doikov, Yurii Nesterov
In this paper, we develop new affine-invariant algorithms for solving composite convex minimization problems with bounded domain. We present a general framework of Contracting-Poin…
Convex optimization based on global lower second-order models
Nikita Doikov, Yurii Nesterov
In this paper, we present new second-order algorithms for composite convex optimization, called Contracting-domain Newton methods. These algorithms are affine-invariant and based o…
New Results on Superlinear Convergence of Classical Quasi-Newton Methods
Anton Rodomanov, Yurii Nesterov
We present a new theoretical analysis of local superlinear convergence of classical quasi-Newton methods from the convex Broyden class. As a result, we obtain a significant improve…
Rates of superlinear convergence for classical quasi-Newton methods
Anton Rodomanov, Yurii Nesterov
We study the local convergence of classical quasi-Newton methods for nonlinear optimization. Although it was well established a long time ago that asymptotically these methods conv…
Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Peter Richtárik +1
In this paper, we propose a new randomized second-order optimization algorithm---Stochastic Subspace Cubic Newton (SSCN)---for minimizing a high dimensional convex function . Ou…
Inexact Tensor Methods with Dynamic Accuracies
Nikita Doikov, Yurii Nesterov
In this paper, we study inexact high-order Tensor Methods for solving convex optimization problems with composite objective. At every step of such methods, we use approximate solut…