2021
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Stelios Triantafyllou, Adish Singla, Goran Radanovic. 2021.
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making.
To appear: In Proceedings of the 35th Annual Conference on Neural Information Processing Systems (NeurIPS'21).
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Kiarash Banihashem, Adish Singla, Goran Radanovic. 2021.
Defense Against Reward Poisoning Attacks in Reinforcement Learning.
arXiv:2102.05776.
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Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla. 2021.
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks.
Journal of Machine Learning Research (JMLR), 22(210): 1-45.
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Rati Devidze, Goran Radanovic, Parameswaran Kamalaruban, Adish Singla. 2021.
Explicable Reward Design for Reinforcement Learning Agents.
To appear: In Proceedings of the 35th Annual Conference on Neural Information Processing Systems (NeurIPS'21).
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Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla. 2021.
Bayesian Persuasion in Sequential Decision-Making.
arXiv:2106.05137.
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Paul Tylkin, Goran Radanovic, David C. Parkes. 2021.
Learning robust helpful behaviors in two-player cooperative Atari environments.
In Proceedings of the 20th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'21).
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Abraham Bernstein, Claes H. de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Möller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger. 2021.
Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482).
Dagstuhl Manifestos, 9(1): 43-61.
2020
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Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla. 2020.
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning.
In Proceedings of the 37th International Conference on Machine Learning (ICML'20).
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Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. 2019.
How do Fairness Definitions Fare? Testing Public Attitudes Towards Three Algorithmic Definitions of Fairness in Loan Allocations.
Artificial Intelligence, 283:103238.
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Debmalya Mandal, Goran Radanovic, David C. Parkes. 2020.
The Effectiveness of Peer Prediction in Long-Term Forecasting.
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20).
2019
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Christos Dimitrakakis, Yang Liu, David C. Parkes, and Goran Radanovic. 2019.
Bayesian Fairness.
In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19).
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Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. 2019.
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness.
In Proceedings of the AAAI/ACM conference on Artificial Intelligence, Ethics, and Society (AIES'19).
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Goran Radanovic, Rati Devidze, David C. Parkes, and Adish Singla. 2019.
Learning to Collaborate in Markov Decision Processes.
In Proceedings of the 36th International Conference on Machine Learning (ICML'19).
2018
2017
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Boi Faltings and Goran Radanovic. 2017.
Game Theory for Data Science: Eliciting Truthful Information.
Morgan & Claypool Publishers.
- Boi Faltings and Goran Radanovic. 2017.
Mechanismen zur Beschaffung korrekter Daten.
Informatik-Spektrum, 40, Pp. 64–74.
- Christos Dimitrakakis, David C. Parkes, Goran Radanovic, and Paul Tylkin. 2017.
Multi-View Decision Processes: The Helper-AI Problem. In Proceedings of
the 31st Annual Conference on Neural Information Processing Systems (NeurIPS'17).
- Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes. 2017.
Calibrated Fairness in Bandits.
The 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017).
- Boi Faltings, Radu Jurca, and Goran Radanovic. 2017.
Peer Truth Serum: Incentives for Crowdsourcing Measurements and Opinions.
arXiv:1704.05269.
2016
2015
2014
2013