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SPIN-RSCI: 4816-2082
ORCID: 0000-0002-8807-5132
ResearcherID: D-7398-2012
Scopus AuthorID: 36024123400
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V. V. Podolskii
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Anton Osokin

  • Anton Osokin has been at HSE since 2017.

Education and Degrees

  • 2014

    Candidate of Sciences* (PhD) in Discrete Mathematics and Mathematical Cybernetics
    Lomonosov Moscow State University
    Thesis Title: Submodular relaxation for energy minimization in Markov random fields

  • 2010

    Diploma in Applied Mathematics and Computer Science
    Lomonosov Moscow State University, Computational Mathematics and Cybernetics

* Candidate of Sciences
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.

Employment history

École Normale Supérieure & INRIA, Paris, France
Computer Science Department
Postdoctoral researcher in WILLOW project-team
October 2016 – August 2017

École Normale Supérieure & INRIA, Paris, France
Computer Science Department
Postdoctoral researcher in SIERRA project-team
October 2014 – September 2016

Moscow State University, Moscow, Russia
Faculty of Computational Mathematics and Cybernetics
Assistant in the department of mathematical methods of forecasting
October 2012 –September 2014
 

Publications

20172

20162

20153

20142

20131

Chapter Kohli P., Osokin A., Jegelka S. A Principled Deep Random Field Model for Image Segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013). Portland : IEEE, 2013. P. 1971-1978. doi

20122

20111

Chapter Osokin A., Vetrov D., Kolmogorov V. Submodular decomposition framework for inference in associative Markov networks with global constraints, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011). Colorado Springs : IEEE, 2011. P. 1889-1896. doi

20101

Chapter Delong A., Osokin A., Isack H. N., Boykov Y. Fast approximate energy minimization with label costs, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010). San Francisco : IEEE, 2010. P. 2173-2180. doi

Timetable for today

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How to Adjust a Smaller Size Neural Network without Quality Loss

Staff members of the HSE Faculty of Computer Science recently presented their papers at the biggest international conference on machine learning, Neural Information Processing Systems (NIPS)’.

How to Adjust a Smaller Size Neural Network without Quality Loss

Staff members of the HSE Faculty of Computer Science recently presented their papers at the biggest international conference on machine learning, Neural Information Processing Systems (NIPS)’.

Welcome Aboard: Tenure-Track Introductions

Every year The HSE Look continues its tradition of welcoming newly recruited international faculty via short summaries about their positions and research interests. In the 34th issue we introduce the tenure-track faculty members, and in November you can learn more about post-doctoral researchers who are starting their work at HSE this fall.