42 citations · 55 across the 6 of their papers we have counts for
7 papers
Study on Precoding Optimization Algorithms in Massive MIMO System with Multi-Antenna Users
Evgeny Bobrov, Dmitry Kropotov, Sergey Troshin +1
The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless multiple input and multiple output (MIMO) systems. In our work, we approximate…
Massive MIMO Adaptive Modulation and Coding Using Online Deep Learning Algorithm
Evgeny Bobrov, Dmitry Kropotov, Hao Lu +1
The paper describes an online deep learning algorithm (ODL) for adaptive modulation and coding in massive MIMO. The algorithm is based on a fully connected neural network, which is…
MARS: Masked Automatic Ranks Selection in Tensor Decompositions
Maxim Kodryan, Dmitry Kropotov, Dmitry Vetrov
Tensor decomposition methods have proven effective in various applications, including compression and acceleration of neural networks. At the same time, the problem of determining…
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…
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…
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…
Faster variational inducing input Gaussian process classification
Pavel Izmailov, Dmitry Kropotov
Gaussian processes (GP) provide a prior over functions and allow finding complex regularities in data. Gaussian processes are successfully used for classification/regression proble…