activity
20132026
most citedGreedy Approach for Low-Rank Matrix Recovery

3 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

math.PR2026

On the Strong Law of Large Numbers under Sublinear Expectations

I. V. Kozlov

A strong law of large numbers (SLLN) for sublinear expectation under a certain integrability condition is proved. It is shown that the proposed integrability condition is weaker th…

math.PR2025

On strong law of large numbers for non identically distributed random variables

I. V. Kozlov, A. Yu. Veretennikov

A new version of a strong law of large numbers for a ``good'' pairwise independent sequence of random variables (r.v.'s) with a small part of ``bad'' dependent r.v.'s is proposed.…

cs.LG2013

Fast greedy algorithm for subspace clustering from corrupted and incomplete data

Alexander Petukhov, Inna Kozlov

We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subsp…

math.NA2013★ 1 cited

Greedy Approach for Subspace Clustering from Corrupted and Incomplete Data

Alexander Petukhov, Inna Kozlov

We describe the Greedy Sparse Subspace Clustering (GSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces f…

math.NA2013★ 3 cited

Correcting Errors in Linear Measurements and Compressed Sensing of Multiple Sources

Alexander Petukhov, Inna Kozlov

We present an algorithm for finding sparse solutions of the system of linear equations with rectangular matrices of size , where , when…

math.NA2013★ 3 cited

Greedy Approach for Low-Rank Matrix Recovery

Alexander Petukhov, Inna Kozlov

We describe the Simple Greedy Matrix Completion Algorithm providing an efficient method for restoration of low-rank matrices from incomplete corrupted entries. We provide numerical…