Alexander Shekhovtsov

According to our database, Alexander Shekhovtsov authored at least 39 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Randomized Lifting to Semi-Structured Communication Complexity via Linear Diversity.

Vladimir Podolskii, Alexander Shekhovtsov

Electron. Colloquium Comput. Complex., 2024

Symmetric Equilibrium Learning of VAEs.

Boris Flach, Dmitrij Schlesinger, Alexander Shekhovtsov

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Enumerating Complexity Revisited.

Alexander Shekhovtsov, Georgii Zakharov

Electron. Colloquium Comput. Complex., 2023

Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator.

Alexander Shekhovtsov

Proceedings of the International Conference on Machine Learning, 2023

Generalized Differentiable RANSAC.

Tong Wei, Yash Patel, Alexander Shekhovtsov, Jirí Matas, Daniel Barath

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

VAE Approximation Error: ELBO and Exponential Families.

Alexander Shekhovtsov, Dmitrij Schlesinger, Boris Flach

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

VAE Approximation Error: ELBO and Conditional Independence.

Dmitrij Schlesinger, Alexander Shekhovtsov, Boris Flach

CoRR, 2021

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.

Alexander Shekhovtsov, Viktor Yanush

Proceedings of the Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28, 2021

Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.

Alexander Shekhovtsov

Proceedings of the Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28, 2021

Initialization and Transfer Learning of Stochastic Binary Networks From Real-Valued Ones.

Anastasiia Livochka, Alexander Shekhovtsov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.

Viktor Yanush, Alexander Shekhovtsov, Dmitry Molchanov, Dmitry P. Vetrov

CoRR, 2020

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks.

Alexander Shekhovtsov, Viktor Yanush, Boris Flach

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems.

Patrick Knöbelreiter, Christian Sormann, Alexander Shekhovtsov, Friedrich Fraundorfer, Thomas Pock

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization.

Siddharth Tourani, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers.

Alexander Shekhovtsov, Boris Flach

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Maximum Persistency via Iterative Relaxed Inference in Graphical Models.

Alexander Shekhovtsov, Paul Swoboda, Bogdan Savchynskyy

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Feed-forward Uncertainty Propagation in Belief and Neural Networks.

Alexander Shekhovtsov, Boris Flach, Michal Busta

CoRR, 2018

Normalization of Neural Networks using Analytic Variance Propagation.

Alexander Shekhovtsov, Boris Flach

CoRR, 2018

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models.

Siddharth Tourani, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Computer Vision - ECCV 2018, 2018

Stochastic Normalizations as Bayesian Learning.

Alexander Shekhovtsov, Boris Flach

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

Generative learning for deep networks.

Boris Flach, Alexander Shekhovtsov, Ondrej Fikar

CoRR, 2017

Scalable Full Flow with Learned Binary Descriptors.

Gottfried Munda, Alexander Shekhovtsov, Patrick Knöbelreiter, Thomas Pock

Proceedings of the Pattern Recognition - 39th German Conference, 2017

End-to-End Training of Hybrid CNN-CRF Models for Stereo.

Patrick Knöbelreiter, Christian Reinbacher, Alexander Shekhovtsov, Thomas Pock

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Partial Optimality by Pruning for MAP-Inference with General Graphical Models.

Paul Swoboda, Alexander Shekhovtsov, Jörg Hendrik Kappes, Christoph Schnörr, Bogdan Savchynskyy

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Automated integer programming based separation of arteries and veins from thoracic CT images.

Christian Payer, Michael Pienn, Zoltán Bálint, Alexander Shekhovtsov, Emina Talakic, Eszter Nagy, Andrea Olschewski, Horst Olschewski, Martin Urschler

Medical Image Anal., 2016

Higher order maximum persistency and comparison theorems.

Alexander Shekhovtsov

Comput. Vis. Image Underst., 2016

Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization.

Alexander Shekhovtsov, Christian Reinbacher, Gottfried Graber, Thomas Pock

CoRR, 2016

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization.

Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Complexity of Discrete Energy Minimization Problems.

Mengtian Li, Alexander Shekhovtsov, Daniel Huber

Proceedings of the Computer Vision - ECCV 2016, 2016

2014

Maximum Persistency in Energy Minimization.

Alexander Shekhovtsov

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel.

Alexander Shekhovtsov, Václav Hlavác

Int. J. Comput. Vis., 2013

2012

Curvature Prior for MRF-Based Segmentation and Shape Inpainting.

Alexander Shekhovtsov, Pushmeet Kohli, Carsten Rother

Proceedings of the Pattern Recognition, 2012

2011

On Partial Opimality by Auxiliary Submodular Problems

Alexander Shekhovtsov, Václav Hlavác

CoRR, 2011

2010

Joint Image GMM and Shading MAP Estimation.

Alexander Shekhovtsov, Václav Hlavác

Proceedings of the 20th International Conference on Pattern Recognition, 2010

2009

Scalable multi-view stereo.

Michal Jancosek, Alexander Shekhovtsov, Tomás Pajdla

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

2008

Efficient MRF deformation model for non-rigid image matching.

Alexander Shekhovtsov, Ivan Kovtun, Václav Hlavác

Comput. Vis. Image Underst., 2008

On partial optimality in multi-label MRFs.

Pushmeet Kohli, Alexander Shekhovtsov, Carsten Rother, Vladimir Kolmogorov, Philip H. S. Torr

Proceedings of the Machine Learning, 2008

A discrete search method for multi-modal non-rigid image registration.

Alexander Shekhovtsov, Juan D. García-Arteaga, Tomás Werner

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

2004

A Higher Order MRF-Model for Stereo-Reconstruction.

Dmitrij Schlesinger, Boris Flach, Alexander Shekhovtsov

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004