Alexander Vezhnevets

According to our database, Alexander Vezhnevets authored at least 29 papers between 2007 and 2023.

Collaborative distances:

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

2023

Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia.

Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon, Ron Ziv, Jayd Matyas, Edgar A. Duéñez-Guzmán, William A. Cunningham, Simon Osindero, Danny Karmon, Joel Z. Leibo

CoRR, 2023

Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition.

Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Melting Pot 2.0.

John P. Agapiou, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Jayd Matyas, Yiran Mao, Peter Sunehag, Raphael Köster, Udari Madhushani, Kavya Kopparapu, Ramona Comanescu, DJ Strouse, Michael Bradley Johanson, Sukhdeep Singh, Julia Haas, Igor Mordatch, Dean Mobbs, Joel Z. Leibo

CoRR, 2022

Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria.

Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets, John P. Agapiou, Kevin R. McKee, Richard Everett, Janusz Marecki, Joel Z. Leibo, Thore Graepel

CoRR, 2022

2021

Statistical discrimination in learning agents.

Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo

CoRR, 2021

A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings.

Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leibo

CoRR, 2021

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot.

Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning.

Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

Options as responses: Grounding behavioural hierarchies in multi-agent RL.

Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo

CoRR, 2019

2017

StarCraft II: A New Challenge for Reinforcement Learning.

Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John P. Agapiou, Julian Schrittwieser, John Quan, Stephen Gaffney, Stig Petersen, Karen Simonyan, Tom Schaul, Hado van Hasselt, David Silver, Timothy P. Lillicrap, Kevin Calderone, Paul Keet, Anthony Brunasso, David Lawrence, Anders Ekermo, Jacob Repp, Rodney Tsing

CoRR, 2017

FeUdal Networks for Hierarchical Reinforcement Learning.

Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Strategic Attentive Writer for Learning Macro-Actions.

Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu

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

2015

Looking out of the window: object localization by joint analysis of all windows in the image.

Alexander Vezhnevets, Vittorio Ferrari

CoRR, 2015

Context Forest for efficient object detection with large mixture models.

Davide Modolo, Alexander Vezhnevets, Vittorio Ferrari

CoRR, 2015

Joint calibration of Ensemble of Exemplar SVMs.

Davide Modolo, Alexander Vezhnevets, Olga Russakovsky, Vittorio Ferrari

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

An active search strategy for efficient object class detection.

Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Object localization in ImageNet by looking out of the window.

Alexander Vezhnevets, Vittorio Ferrari

Proceedings of the British Machine Vision Conference 2015, 2015

Context Forest for Object Class Detection.

Davide Modolo, Alexander Vezhnevets, Vittorio Ferrari

Proceedings of the British Machine Vision Conference 2015, 2015

2014

An active search strategy for efficient object detection.

Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari

CoRR, 2014

Associative Embeddings for Large-Scale Knowledge Transfer with Self-Assessment.

Alexander Vezhnevets, Vittorio Ferrari

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

2013

Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI.

Dwarikanath Mahapatra, Alexander Vezhnevets, Peter J. Schüffler, Jeroen A. W. Tielbeek, Franciscus M. Vos, Joachim M. Buhmann

Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

2012

Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections.

Dmitry Laptev, Alexander Vezhnevets, Sarvesh Dwivedi, Joachim M. Buhmann

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Weakly supervised structured output learning for semantic segmentation.

Alexander Vezhnevets, Vittorio Ferrari, Joachim M. Buhmann

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Active learning for semantic segmentation with expected change.

Alexander Vezhnevets, Joachim M. Buhmann, Vittorio Ferrari

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Weakly supervised semantic segmentation with a multi-image model.

Alexander Vezhnevets, Vittorio Ferrari, Joachim M. Buhmann

Proceedings of the IEEE International Conference on Computer Vision, 2011

Agnostic Domain Adaptation.

Alexander Vezhnevets, Joachim M. Buhmann

Proceedings of the Pattern Recognition - 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31, 2011

2010

Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning.

Alexander Vezhnevets, Joachim M. Buhmann

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2007

Avoiding Boosting Overfitting by Removing Confusing Samples.

Alexander Vezhnevets, Olga Barinova

Proceedings of the Machine Learning: ECML 2007, 2007