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D-Index & Metrics

Computer Science

D-Index
52
Citations
42378
World Ranking
4935
National Ranking
34

Overview

Vladimir Kolmogorov is affiliated with the Institute of Science and Technology Austria in Austria. Their research spans multiple areas within computer science and mathematics, with a focus on computational theory and mathematics. The primary fields of study include computer science and mathematics, with significant contributions to the subfields of computational theory and mathematics, artificial intelligence, numerical analysis, computer vision and pattern recognition, and statistics and probability.

Their main topics of work cover:

  • Advanced Optimization Algorithms Research
  • Bayesian Methods and Mixture Models
  • Complexity and Algorithms in Graphs
  • Advanced Graph Theory Research
  • Advanced Combinatorial Mathematics
  • Advanced Algebra and Logic
  • Computational Geometry and Mesh Generation

Vladimir Kolmogorov has produced a range of recent publications, including:

  • Parameter Estimation for Gibbs Distributions, 2024, ACM Transactions on Algorithms
  • One-sided Frank-Wolfe algorithms for saddle problems, 2021, arXiv (Cornell University)
  • Generalized minimum 0-extension problem and discrete convexity, 2021, arXiv (Cornell University)
  • A New Notion of Commutativity for the Algorithmic Lovász Local Lemma, 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • A new notion of commutativity for the algorithmic Lovász Local Lemma, 2020, arXiv (Cornell University)

Their work has been published in several venues, notably:

  • arXiv (Cornell University)
  • ACM Transactions on Algorithms
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Mathematical Programming
  • SIAM Journal on Optimization

Frequent coauthors collaborating with Vladimir Kolmogorov include:

  • David G. Harris
  • Martin Dvorak
  • Fotis Iliopoulos
  • Simone Naldi
  • Jeferson Zapata

Best Publications

  • "GrabCut": interactive foreground extraction using iterated graph cuts

    Carsten Rother;Vladimir Kolmogorov;Andrew Blake

  • An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision

    Y. Boykov;V. Kolmogorov

  • What energy functions can be minimized via graph cuts

    V. Kolmogorov;R. Zabin

  • What energy functions can be minimized via graph cuts?

    Unknown

  • Convergent Tree-Reweighted Message Passing for Energy Minimization

    V. Kolmogorov

  • Computing visual correspondence with occlusions using graph cuts

    V. Kolmogorov;R. Zabih

  • A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors

    R. Szeliski;R. Zabih;D. Scharstein;O. Veksler

  • Multi-camera Scene Reconstruction via Graph Cuts

    Vladimir Kolmogorov;Ramin Zabih

  • Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs

    C. Rother;T. Minka;A. Blake;V. Kolmogorov

  • Optimizing Binary MRFs via Extended Roof Duality

    C. Rother;V. Kolmogorov;V. Lempitsky;M. Szummer

  • Blossom V: a new implementation of a minimum cost perfect matching algorithm

    Vladimir Kolmogorov

  • Minimizing Nonsubmodular Functions with Graph Cuts-A Review

    V. Kolmogorov;C. Rother

  • Graph cut based image segmentation with connectivity priors

    S. Vicente;V. Kolmogorov;C. Rother

  • A comparative study of energy minimization methods for markov random fields

    Richard Szeliski;Ramin Zabih;Daniel Scharstein;Olga Veksler

  • Feature Correspondence Via Graph Matching: Models and Global Optimization

    Lorenzo Torresani;Vladimir Kolmogorov;Carsten Rother

  • Bilayer Segmentation of Live Video

    A. Criminisi;G. Cross;A. Blake;V. Kolmogorov

  • Object cosegmentation

    Sara Vicente;Carsten Rother;Vladimir Kolmogorov

  • Proofs of Space

    Stefan Dziembowski;Sebastian Faust;Vladimir Kolmogorov;Krzysztof Z Pietrzak

  • Bi-layer segmentation of binocular stereo video

    V. Kolmogorov;A. Criminisi;A. Blake;G. Cross

  • What metrics can be approximated by geo-cuts, or global optimization of length/area and flux

    V. Kolmogorov;Y. Boykov

  • Spatially coherent clustering using graph cuts

    R. Zabih;V. Kolmogorov

  • GrabCut: Interactive Foreground Extraction Using Iterated Graph Cuts

    Unknown

Frequent Co-Authors

Carsten Rother
Carsten Rother Heidelberg University
Andrew Blake
Andrew Blake University of Cambridge
Ramin Zabih
Ramin Zabih Cornell University
Antonio Criminisi
Antonio Criminisi Microsoft (United States)
Yuri Boykov
Yuri Boykov University of Waterloo
Christoph H. Lampert
Christoph H. Lampert Institute of Science and Technology Austria
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Thomas Pock
Thomas Pock Graz University of Technology
Krzysztof Pietrzak
Krzysztof Pietrzak Institute of Science and Technology Austria

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