Anton Osokin

47 papers A* 8A 3Journal 21Unranked 15
YearRankTypeTitle / Venue / Authors
2023 — conf
Searching for Better Database Queries in the Outputs of Semantic Parsers.
EACL (Findings)
Anton Osokin, Irina Saparina, Ramil Yarullin
2022 J jnl
Searching for Better Database Queries in the Outputs of Semantic Parsers.
CoRR
Anton Osokin, Irina Saparina, Ramil Yarullin
2021 — conf
SPARQLing Database Queries from Intermediate Question Decompositions.
EMNLP (1)
Irina Saparina, Anton Osokin
2021 J jnl
SPARQLing Database Queries from Intermediate Question Decompositions.
CoRR
Irina Saparina, Anton Osokin
2020 — conf
OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features.
ECCV (15)
Anton Osokin, Denis Sumin, Vasily Lomakin
2020 J jnl
OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features.
CoRR
Anton Osokin, Denis Sumin, Vasily Lomakin
2019 J jnl
Cost-Sensitive Training for Autoregressive Models.
CoRR
Irina Saparina, Anton Osokin
2019 — conf
How to Put Algorithms into Neural Networks.
DAMDID/RCDL
Anton Osokin
2019 — conf
Performance and Scalability of Materials Science and Machine Learning Codes on the State-of-Art Hybrid Supercomputer Architecture.
RuSCDays
Nikolay Kondratyuk, Grigory S. Smirnov, Alexander Agarkov, Anton Osokin, Vsevolod P. Nikolskiy, Alexander Semenov, Vladimir V. Stegailov
2019 J jnl
Scaling Matters in Deep Structured-Prediction Models.
CoRR
Aleksandr Shevchenko, Anton Osokin
2019 — conf
Three Simple Approaches to Combining Neural Networks with Algorithms.
DAMDID/RCDL (Selected Papers)
Anton Osokin
2018 A conf
Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models.
UAI
Tatiana Shpakova, Francis R. Bach, Anton Osokin
2018 J jnl
Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models.
CoRR
Tatiana Shpakova, Francis R. Bach, Anton Osokin
2018 J jnl
Modeling Spatio-Temporal Human Track Structure for Action Localization.
CoRR
Guilhem Chéron, Anton Osokin, Ivan Laptev, Cordelia Schmid
2018 A* conf
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates.
NeurIPS
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
2018 J jnl
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates.
CoRR
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
2018 — conf
SEARNN: Training RNNs with global-local losses.
ICLR (Poster)
Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien
2018 J jnl
Tube-CNN: Modeling temporal evolution of appearance for object detection in video.
CoRR
Tuan-Hung Vu, Anton Osokin, Ivan Laptev
2017 A* conf
GANs for Biological Image Synthesis.
ICCV
Anton Osokin, Anatole Chessel, Rafael Edgardo Carazo-Salas, Federico Vaggi
2017 J jnl
GANs for Biological Image Synthesis.
CoRR
Anton Osokin, Anatole Chessel, Rafael Edgardo Carazo-Salas, Federico Vaggi
2017 — conf
On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
NIPS
Anton Osokin, Francis R. Bach, Simon Lacoste-Julien
2017 J jnl
On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
CoRR
Anton Osokin, Francis R. Bach, Simon Lacoste-Julien
2017 J jnl
SEARNN: Training RNNs with Global-Local Losses.
CoRR
Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien
2016 A conf
Breaking Sticks and Ambiguities with Adaptive Skip-gram.
AISTATS
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
2016 A conf
Deep Part-Based Generative Shape Model with Latent Variables.
BMVC
Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry P. Vetrov
2016 A* conf
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs.
ICML
Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Kumar Dokania, Simon Lacoste-Julien
2016 J jnl
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs.
CoRR
Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Kumar Dokania, Simon Lacoste-Julien
2015 J jnl
Breaking Sticks and Ambiguities with Adaptive Skip-gram.
CoRR
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
2015 A* conf
Context-Aware CNNs for Person Head Detection.
ICCV
Tuan-Hung Vu, Anton Osokin, Ivan Laptev
2015 J jnl
Context-aware CNNs for person head detection.
CoRR
Tuan-Hung Vu, Anton Osokin, Ivan Laptev
2015 J jnl
Submodular Relaxation for Inference in Markov Random Fields.
IEEE Trans. Pattern Anal. Mach. Intell.
Anton Osokin, Dmitry P. Vetrov
2015 J jnl
Submodular relaxation for inference in Markov random fields.
CoRR
Anton Osokin, Dmitry P. Vetrov
2015 — conf
Tensorizing Neural Networks.
NIPS
Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2015 J jnl
Tensorizing Neural Networks.
CoRR
Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2014 — conf
Multi-utility Learning: Structured-Output Learning with Multiple Annotation-Specific Loss Functions.
EMMCVPR
Roman Shapovalov, Dmitry P. Vetrov, Anton Osokin, Pushmeet Kohli
2014 J jnl
Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions.
CoRR
Roman Shapovalov, Dmitry P. Vetrov, Anton Osokin, Pushmeet Kohli
2014 — conf
Perceptually Inspired Layout-Aware Losses for Image Segmentation.
ECCV (2)
Anton Osokin, Pushmeet Kohli
2014 A* conf
Putting MRFs on a Tensor Train.
ICML
Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry P. Vetrov
2013 A* conf
A Principled Deep Random Field Model for Image Segmentation.
CVPR
Pushmeet Kohli, Anton Osokin, Stefanie Jegelka
2012 J jnl
Fast Approximate Energy Minimization with Label Costs.
Int. J. Comput. Vis.
Andrew Delong, Anton Osokin, Hossam N. Isack, Yuri Boykov
2012 — conf
Minimizing Sparse High-Order Energies by Submodular Vertex-Cover.
NIPS
Andrew Delong, Olga Veksler, Anton Osokin, Yuri Boykov
2012 — conf
Submodular Relaxation for MRFs with High-Order Potentials.
ECCV Workshops (3)
Anton Osokin, Dmitry P. Vetrov
2011 J jnl
Submodular Decomposition Framework for Inference in Associative Markov Networks with Global Constraints
CoRR
Anton Osokin, Dmitry P. Vetrov, Vladimir Kolmogorov
2011 A* conf
Submodular decomposition framework for inference in associative Markov networks with global constraints.
CVPR
Anton Osokin, Dmitry P. Vetrov, Vladimir Kolmogorov
2010 — conf
An Interactive Method of Anatomical Segmentation and Gene Expression Estimation for an Experimental Mouse Brain Slice.
CIBB
Anton Osokin, Dmitry P. Vetrov, Alexey Lebedev, Vladimir Galatenko, Dmitry Kropotov, Konstantin V. Anokhin
2010 A* conf
Fast approximate energy minimization with label costs.
CVPR
Andrew Delong, Anton Osokin, Hossam N. Isack, Yuri Boykov
2009 — conf
3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas.
CIBB
Anton Osokin, Dmitry P. Vetrov, Dmitry Kropotov