10 citations · 10 across the 2 of their papers we have counts for
3 papers
math.OC2019
A Randomized Coordinate Descent Method with Volume Sampling
Anton Rodomanov, Dmitry Kropotov
We analyze the coordinate descent method with a new coordinate selection strategy, called volume sampling. This strategy prescribes selecting subsets of variables of certain size p…
stat.ML2019
Hamiltonian Monte-Carlo for Orthogonal Matrices
Viktor Yanush, Dmitry Kropotov
We consider the problem of sampling from posterior distributions for Bayesian models where some parameters are restricted to be orthogonal matrices. Such matrices are sometimes use…
cs.LG2017★ 10 cited
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
We propose a method (TT-GP) for approximate inference in Gaussian Process (GP) models. We build on previous scalable GP research including stochastic variational inference based on…