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Anton Osokin
(October 2016)
Curriculum Vitae
CONTACT
INFORMATION
WILLOW project-team
INRIA
2 rue Simone Iff
Voie DQ12
Paris, 75012, France
RESEARCH
INTERESTS
Machine learning, structured prediction, computer vision, deep learning,
discrete optimization
EDUCATION
Ph.D. in physics and mathematics (кандидат физ.-мат. наук)
Moscow State University, Moscow, Russia
Dissertation title: Submodular relaxation for energy minimization in Markov
random fields
Advisor: Dr. Dmitry Vetrov
September 2010 – May 2014
Web: http://www.di.ens.fr/∼aosokin
Specialist (M.Sc. equivalent) in Applied Mathematics (with honours),
Moscow State University, Moscow, Russia
Department of Computational Mathematics and Cybernetics
Advisor: Dr. Dmitry Vetrov
September 2005 – June 2010
EMPLOYMENT
École Normale Supérieure & INRIA, Paris, France
Computer Science Department
Postdoctoral researcher in WILLOW project-team
October 2016 – . . .
École Normale Supérieure & INRIA, Paris, France
Computer Science Department
Postdoctoral researcher in SIERRA project-team
October 2014 – September 2016
Moscow State University, Moscow, Russia
Department of Computational Mathematics and Cybernetics
Assistant in Research group of Bayesian Methods in Machine Learning
October 2012 –September 2014
Microsoft Research, Cambridge, UK
Machine Learning and Perception
Research intern
July 2012 – September 2012
University of Western Ontario, London, Canada
Computer Science Department
Visiting researcher in Vision Research Group
June 2009 – August 2009, January 2010 – March 2010
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PUBLICATIONS Refereed Journal Articles
A. Osokin, D. Vetrov. Submodular relaxation for inference in Markov
random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 37(7): 1347–1359, 2015.
A. Delong∗ , A. Osokin∗ , H. Isack, Y. Boykov. Fast Approximate Energy
Minimization with Label Costs. International Journal of Computer Vision
(IJCV), 96(1):1–27, 2012.
D. Kropotov, D. Laptev, A. Osokin, D. Vetrov. Variational segmentation algorithms with label frequency constraints. Pattern Recognition and
Image Analysis, 20(3):324–334, 2010.
Refereed Conference Proceedings
A. Osokin∗ , J.-B. Alayrac∗ , P. Dokania, S. Lacoste-Julien. Minding the
Gaps for Block Frank-Wolfe Optimization of Structured SVM. Proceedings
of the International Conference on Machine Learning (ICML), 2016.
S. Bartunov, D. Kondrashkin, A. Osokin, D. Vetrov. Breaking Sticks and
Ambiguities with Adaptive Skip-gram. Proceedings of the International
Conference on Artificial Intelligence and Statistics (AISTATS), 2016.
A. Kirillov, M. Gavrikov, E. Lobacheva, A. Osokin, D. Vetrov. Deep
Part-Based Generative Shape Model with Latent Variables. Proceedings
of the British Machine Vision Conference (BMVC), 2016.
T.-H. Vu, A. Osokin, I. Laptev. Context-aware CNNs for person head detection. Proceedings of the International Conference on Computer Vision
(ICCV), 2015.
A. Novikov, D. Podoprikhin, A. Osokin, D. Vetrov. Tensorizing Neural
Networks. Advances in Neural Information Processing Systems (NIPS),
2015.
R. Shapovalov, D. Vetrov, A. Osokin, P. Kohli. Multi-utility Learning:
Structured-Output Learning with Multiple Annotation-Specific Loss Functions. Proceedings of the International Conference on Energy Minimization
Methods in Computer Vision and Pattern Recognition (EMMCVPR),
2015.
A. Osokin, P. Kohli. Perceptually Inspired Layout-aware Losses for Image Segmentation. Proceedings of the European Conference on Computer
Vision (ECCV), 2014.
A. Novikov, A. Rodomanov, A. Osokin, D. Vetrov. Putting MRFs on
a Tensor Train. Proceedings of the International Conference on Machine
Learning (ICML), 2014.
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P. Kohli, A. Osokin, S. Jegelka. A Principled Deep Random Field Model
for Image Segmentation. Proceedings of the international conference on
Computer Vision and Pattern Recognition (CVPR), 2013.
A. Delong, O. Veksler, A. Osokin, Y. Boykov. Minimizing Sparse HighOrder Energies by Submodular Vertex-Cover. Advances in Neural Information Processing Systems (NIPS), 2012.
A. Osokin, D. Vetrov, V. Kolmogorov. Submodular Decomposition Framework for Inference in MRF with Global Constraints. Proceedings of the international conference on Computer Vision and Pattern Recognition (CVPR),
2011.
A. Delong∗ , A. Osokin∗ , H. Isack, Y. Boykov. Fast Approximate Energy
Minimization with Label Costs. Proceedings of the international conference on Computer Vision and Pattern Recognition (CVPR), 2010.
Other publications
P. Kohli, A. Osokin and S. Jegelka. A principled deep random field for
image segmentation. NIPS Workshop on Discrete Optimization in Machine learning (DISCML NIPS), 2012.
A. Osokin, D. Vetrov. Submodular Relaxation for MRFs with High-Order
Potentials. Computer Vision – ECCV 2012. Workshops and Demonstrations. Lecture Notes in Computer Science Volume 7585, 2012, pp. 305–
314.
D. Vetrov, A. Osokin. Graph Preserving Label Decomposition in Discrete
MRFs with Selfish Potentials. NIPS Workshop on Discrete Optimization
in Machine learning (DISCML NIPS), 2011.
A. Osokin, D. Vetrov, A. Lebedev, V. Galatenko, D. Kropotov, K. Anokhin.
An Interactive Method of Anatomical Segmentation and Gene Expression
Estimation for an Experimental Mouse Brain Slice. R. Rizzo and P.J.G.
Lisboa (Eds.): CIBB 2010, LNBI 6685, pp. 86–97, 2011.
A. Osokin, D. Vetrov, D. Kropotov, 3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas, F.
Masulli, L. Peterson, and R. Tagliaferri (Eds.): CIBB 2009, LNBI 6160,
pp. 291–303, 2010.
A. Osokin, D. Vetrov, D. Kropotov, 3D Reconstruction of Mouse Brain
from a Sequence of 2D Brain Slices. Proceedings of the 14-th Russian conference on Mathematical Methods of Pattern Recognition, Moscow, MAKS
Press, 2009, pp. 582–585. (in Russian)
AWARDS AND
FELLOWSHIPS
Russian President Fellowship for young scientists, 2012–2014
Russian Foundation of Basic Research grant “My First Grant”, 2012–2013
Academia Europaea Prize for Young Scientists, Russian Club of European
Academy Members, 2011
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Best Diploma prize of Moscow State University, Department of Computational Mathematics and Cybernetics, 2010
Best Student Paper Award at Russian conference on Mathematical Methods of Pattern Recognition, 2009
TEACHING
EXPERIENCE
École CentraleSupélec, Châtenay-Malabry, France.
Lecturer, Discrete Optimization. Spring 2016.
Moscow State University, Moscow, Russia.
Instructor of seminars and practical sessions, Graphical models. Spring
2011, Spring 2012, Spring 2013.
Instructor of practical sessions, Machine Learning. Fall 2012, Spring 2013,
Fall 2013, Spring 2014.
Co-organizer of research seminar on Bayesian methods in machine learning. 2011–2014.
Yandex School of Data Analysis, Moscow, Russia.
Instructor of seminars and practical sessions, Graphical models. Fall
2011, Fall 2012, Fall 2013.
Skolkovo Institute of Science and Technology, Moscow, Russia.
Teaching Assistant, Machine Learning. Fall 2013.
SUPERVISION
INRIA, Paris, France.
Tuan-Hung Vu (2015-2016) – Ph.D. student. Co-supervised with Ivan
Laptev.
Yumin Suh (2015) – intern (6 months). Co-supervised with Minsu Cho.
Moscow State University, Moscow, Russia.
Alexander Novikov (2012-2014) – undergraduate student. Co-supervised
with Dmitry Vetrov.
Pavel Novikov (2011) – undergraduate student. Co-supervised with Dmitry
Vetrov.
Andrey Tikhonov (2010) – undergraduate student. Co-supervised with
Dmitry Vetrov.
Anton Golovin (2010) – undergraduate student. Co-supervised with
Dmitry Vetrov.
Yandex School of Data Analysis, Moscow, Russia.
Michael Kolupaev (2013) – M.Sc. student. Advised the M.Sc. thesis.
ACADEMIC
SERVICE
Regularly reviewing for journals:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
International Journal on Computer Vision (IJCV)
Regularly reviewing for conferences:
International conference on Neural Information Processing Systems (NIPS)
International Conference on Machine Learning (ICML)
International Conference on Computer Vision (ICCV)
International conference on Computer Vision and Pattern Recognition
(CVPR)
European Conference on Computer Vision (ECCV)
LANGUAGES
Russian
English
French
Native speaker
Fluent
Beginner
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REFERENCES
Simon Lacoste-Julien
Assistant Professor
Department of Computer Science and Operations Research
Université de Montréal, Montréal, Canada
Web: http://www.di.ens.fr/∼slacoste
Ivan Laptev
Research director
WILLOW project-team
École Normale Supérieure & INRIA, Paris, France
Web: https://www.di.ens.fr/∼laptev
Pushmeet Kohli
Principal Researcher
Cognition Group
Microsoft Research, Redmond, USA
Web: http://research.microsoft.com/en-us/um/people/pkohli
Yuri Boykov
Professor
Vision Research Group
Computer Science Department
University of Western Ontario, London, Canada
Web: http://www.csd.uwo.ca/∼yuri
Dmitry Vetrov
Associate professor
Bayesian Methods research group
National Research University Higher School of Economics, Moscow, Russia
Web: https://cs.hse.ru/en/bayesgroup/people/vetrov
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