815 citations · 3.2k across the 142 of their papers we have counts for
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Preconditioners for hierarchical matrices based on their extended sparse form
Daria Sushnikova, Ivan V. Oseledets
In this paper we consider linear systems with dense-matrices which arise from numerical solution of boundary integral equations. Such matrices can be well-approximated with $\mathc…
Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba +2
We propose a simple two-step approach for speeding up convolution layers within large convolutional neural networks based on tensor decomposition and discriminative fine-tuning. Gi…
Algebraic reputation model RepRank and its application to spambot detection
G. V. Ovchinnikov, D. A. Kolesnikov, I. V. Oseledets
Due to popularity surge social networks became lucrative targets for spammers and guerilla marketers, who are trying to game ranking systems and broadcast their messages at little…
Fast, memory efficient low-rank approximation of SimRank
I. V. Oseledets, G. V. Ovchinnikov
SimRank is a well-known similarity measure between graph vertices. In this paper novel low-rank approximation of SimRank is proposed.
From low-rank approximation to an efficient rational Krylov subspace method for the Lyapunov equation
D. A. Kolesnikov, I. V. Oseledets
We propose a new method for the approximate solution of the Lyapunov equation with rank- right-hand side, which is based on extended rational Krylov subspace approximation with…
Unifying time evolution and optimization with matrix product states
Jutho Haegeman, Christian Lubich, Ivan Oseledets +2
We show that the time-dependent variational principle provides a unifying framework for time-evolution methods and optimisation methods in the context of matrix product states. In…