Scholar
Vladimir Kolmogorov
Google Scholar ID: BBGlIGQAAAAJ
IST Austria
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Citations
6,859
H-index
29
i10-index
50
Publications
20
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0
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Publications
10 items
Near-Optimal Parallel Approximate Counting via Sampling
2026
Cited
0
A Fast Approximation Algorithm for the Minimum Balanced Vertex Separator in a Graph
2026
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0
Greedy matroid base packings with applications to dynamic graph density and orientations
2025
Cited
0
Composition Direction of Seymour's Theorem for Regular Matroids -- Formally Verified
2025
Cited
0
Simple parallel estimation of the partition ratio for Gibbs distributions
2025
Cited
0
A faster algorithm for the k-forest problem: breaking the Ok(n3/2) complexity barrier
arXiv.org · 2024
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0
Bounded indegree k-forests problem and a faster algorithm for directed graph augmentation
arXiv.org · 2024
Cited
1
Duality theory in linear optimization and its extensions - formally verified
arXiv.org · 2024
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0
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Resume (English only)
Background
Main research area is discrete optimization
Specific topics include complexity classifications, especially in Valued Constraint Satisfaction Problems
Designing algorithms for combinatorial optimization problems (e.g., maximum flow, minimum cost perfect matching)
Algorithms for MAP inference in Markov Random Fields
Previously worked on applications of discrete optimization (e.g., graph cuts) in computer vision
Miscellany
Not accepting intern applications at the moment
Open to postdoc applications in discrete optimization
Supervises PhD students and postdocs including Pavel Arkhipov, Martin Dvořák, Jeferson Zapata, etc.
Organized 'Workshop on Optimization in Machine Learning' at IST Austria (May 2020, cancelled due to pandemic)
Affiliated with the European Laboratory for Learning and Intelligent Systems (ELLIS)
Co-authors
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Co-authors: 0 (list not available)
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