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ORCIDAlexander Vezhnevets
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2020 – today
- 2023
[c18]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo:
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. AAMAS 2023: 2827-2829- [i16]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán
, Igor Mordatch, Joel Z. Leibo:
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. CoRR abs/2302.01180 (2023) - [i15]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:
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia. CoRR abs/2312.03664 (2023) - 2022
- [i14]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:
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR abs/2201.01816 (2022) - [i13]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:
Melting Pot 2.0. CoRR abs/2211.13746 (2022) - 2021
- [c17]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. ICML 2021: 6187-6199 - [i12]Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leibo:
A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings. CoRR abs/2106.09012 (2021) - [i11]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. CoRR abs/2107.06857 (2021) - [i10]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:
Statistical discrimination in learning agents. CoRR abs/2110.11404 (2021) - 2020
- [c16]Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo:
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning. ICML 2020: 9733-9742
2010 – 2019
- 2019
- [j1]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:
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - [i9]Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo:
Options as responses: Grounding behavioural hierarchies in multi-agent RL. CoRR abs/1906.01470 (2019) - 2017
- [c15]Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu:
FeUdal Networks for Hierarchical Reinforcement Learning. ICML 2017: 3540-3549 - [i8]Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu:
FeUdal Networks for Hierarchical Reinforcement Learning. CoRR abs/1703.01161 (2017) - [i7]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:
StarCraft II: A New Challenge for Reinforcement Learning. CoRR abs/1708.04782 (2017) - 2016
- [c14]Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu:
Strategic Attentive Writer for Learning Macro-Actions. NIPS 2016: 3486-3494 - [i6]Alexander Vezhnevets, Volodymyr Mnih, John P. Agapiou, Simon Osindero, Alex Graves, Oriol Vinyals, Koray Kavukcuoglu:
Strategic Attentive Writer for Learning Macro-Actions. CoRR abs/1606.04695 (2016) - 2015
- [c13]Alexander Vezhnevets, Vittorio Ferrari:
Object localization in ImageNet by looking out of the window. BMVC 2015: 27.1-27.12 - [c12]Davide Modolo, Alexander Vezhnevets, Vittorio Ferrari:
Context Forest for Object Class Detection. BMVC 2015: 188.1-188.14 - [c11]Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari:
An active search strategy for efficient object class detection. CVPR 2015: 3022-3031 - [c10]Davide Modolo, Alexander Vezhnevets, Olga Russakovsky, Vittorio Ferrari:
Joint calibration of Ensemble of Exemplar SVMs. CVPR 2015: 3955-3963 - [i5]Alexander Vezhnevets, Vittorio Ferrari:
Looking out of the window: object localization by joint analysis of all windows in the image. CoRR abs/1501.01181 (2015) - [i4]Davide Modolo, Alexander Vezhnevets, Olga Russakovsky, Vittorio Ferrari:
Joint calibration of Ensemble of Exemplar SVMs. CoRR abs/1503.00783 (2015) - [i3]Davide Modolo, Alexander Vezhnevets, Vittorio Ferrari:
Context Forest for efficient object detection with large mixture models. CoRR abs/1503.00787 (2015) - 2014
- [c9]Alexander Vezhnevets, Vittorio Ferrari:
Associative Embeddings for Large-Scale Knowledge Transfer with Self-Assessment. CVPR 2014: 1987-1994 - [i2]Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari:
An active search strategy for efficient object detection. CoRR abs/1412.3709 (2014) - 2013
- [c8]Dwarikanath Mahapatra, Alexander Vezhnevets, Peter J. Schüffler, Jeroen A. W. Tielbeek, Franciscus M. Vos, Joachim M. Buhmann:
Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI. ISBI 2013: 844-847 - [i1]Alexander Vezhnevets, Vittorio Ferrari:
Associative embeddings for large-scale knowledge transfer with self-assessment. CoRR abs/1312.3240 (2013) - 2012
- [c7]Alexander Vezhnevets, Vittorio Ferrari, Joachim M. Buhmann:
Weakly supervised structured output learning for semantic segmentation. CVPR 2012: 845-852 - [c6]Alexander Vezhnevets, Joachim M. Buhmann, Vittorio Ferrari:
Active learning for semantic segmentation with expected change. CVPR 2012: 3162-3169 - [c5]Dmitry Laptev, Alexander Vezhnevets, Sarvesh Dwivedi, Joachim M. Buhmann:
Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections. MICCAI (1) 2012: 323-330 - 2011
- [c4]Alexander Vezhnevets, Joachim M. Buhmann:
Agnostic Domain Adaptation. DAGM-Symposium 2011: 376-385 - [c3]Alexander Vezhnevets, Vittorio Ferrari, Joachim M. Buhmann:
Weakly supervised semantic segmentation with a multi-image model. ICCV 2011: 643-650 - 2010
- [c2]Alexander Vezhnevets, Joachim M. Buhmann:
Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning. CVPR 2010: 3249-3256
2000 – 2009
- 2007
- [c1]Alexander Vezhnevets, Olga Barinova:
Avoiding Boosting Overfitting by Removing Confusing Samples. ECML 2007: 430-441
Coauthor Index
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