14 citations · 23 across the 3 of their papers we have counts for
3 papers
math.OC2019★ 14 cited
On Inexact Solution of Auxiliary Problems in Tensor Methods for Convex Optimization
Geovani Nunes Grapiglia, Yurii Nesterov
In this paper we study the auxiliary problems that appear in -order tensor methods for unconstrained minimization of convex functions with -Hölder continuous th derivative…
math.OC2015★ 3 cited
Random block coordinate descent methods for linearly constrained optimization over networks
I. Necoara, Yu. Nesterov, F. Glineur
In this paper we develop random block coordinate gradient descent methods for minimizing large scale linearly constrained separable convex problems over networks. Since we have cou…
math.OC2014★ 6 cited
Learning Supervised PageRank with Gradient-Free Optimization Methods
Lev Bogolubsky, Pavel Dvurechensky, Alexander Gasnikov +5
In this paper, we consider a problem of learning supervised PageRank models, which can account for some properties not considered by classical approaches such as the classical Page…