Radanovic, Goran

Debmalya Mandal, Goran Radanovic, and David C. Parkes. 2020. “The Effectiveness of Peer Prediction in Long-Term Forecasting.” In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020) .
Christos Dimitrakakis, Yang Liu, David C. Parkes, and Goran Radanovic. 2019. “Bayesian Fairness.” In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI). Download
Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David Parkes, and Yang Liu. 2019. “How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness.” In Proceedings of AI Ethics and Society (AIES) , Pp. 99-106. Download
Goran Radanovic, Rati Devidze, David Parkes, and Adish Singla. 2019. “Learning to Collaborate in Markov Decision Processes.” In Proceedings of the 36th International Conference on Machine Learning (ICML'19), Pp. 5261-5270. Download
Goran Radanovic, Adish Singla, Andreas Krause, and Boi Faltings. 2018. “Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints.” In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18). Download
Goran Radanovic and Boi Faltings. 2018. “Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge.” In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18). Download
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C. Parkes. 2017. “Fair Experimentation.” In Conference on Digital Experimentation (CODE).
Boi Faltings and Goran Radanovic. 2017. Game Theory for Data Science: Eliciting Truthful Information. Morgan & Claypool Publishers.
Christos Dimitrakakis, David C. Parkes, Goran Radanovic, and Paul Tylkin. 2017. “Multi-View Decision Processes: The Helper-AI Problem.” In Proc. 30th Advances in Neural Information Processing Systems (NIPS'17), Pp. 5449-5458. Download