| Calibrated fairness in bandits Y Liu, G Radanovic, C Dimitrakakis, D Mandal, DC Parkes Fairness, Accountability, and Transparency in Machine Learning, 2017 | 156 | 2017 |
| Ensuring Fairness Beyond the Training Data D Mandal, S Deng, S Jana, JM Wing, D Hsu Advances in Neural Information Processing Systems 33, 2020 | 89 | 2020 |
| A Truthful Budget Feasible Multi-Armed Bandit Mechanism for Crowdsourcing Time Critical Tasks. A Biswas, S Jain, D Mandal, Y Narahari AAMAS, 1101-1109, 2015 | 72 | 2015 |
| Peer prediction with heterogeneous users A Agarwal, D Mandal, DC Parkes, N Shah ACM Transactions on Economics and Computation (TEAC) 8 (1), 1-34, 2020 | 67 | 2020 |
| Efficient and thrifty voting by any means necessary D Mandal, AD Procaccia, N Shah, D Woodruff Advances in Neural Information Processing Systems 32, 2019 | 65 | 2019 |
| Metalearning with graph neural networks: Methods and applications D Mandal, S Medya, B Uzzi, C Aggarwal ACM SIGKDD Explorations Newsletter 23 (2), 13-22, 2022 | 63 | 2022 |
| Optimal communication-distortion tradeoff in voting D Mandal, N Shah, DP Woodruff Proceedings of the 21st ACM Conference on Economics and Computation, 795-813, 2020 | 55 | 2020 |
| Performative reinforcement learning D Mandal, S Triantafyllou, G Radanovic International Conference on Machine Learning, 23642-23680, 2023 | 32 | 2023 |
| Socially fair reinforcement learning D Mandal, J Gan arXiv preprint arXiv:2208.12584, 2022 | 27 | 2022 |
| Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences A Nika, D Mandal, P Kamalaruban, G Tzannetos, G Radanović, A Singla International Conference on Machine Learning (ICML), 2024 | 25 | 2024 |
| Surprisingly Popular Voting Recovers Rankings, Surprisingly! H Hosseini, D Mandal, N Shah, K Shi IJCAI’21, 2021 | 25 | 2021 |
| Peer Prediction with Heterogeneous Tasks D Mandal, M Leifer, DC Parkes, G Pickard, V Shnayder arXiv preprint arXiv:1612.00928, 2016 | 19 | 2016 |
| Adversarial blocking bandits N Bishop, H Chan, D Mandal, L Tran-Thanh Advances in Neural Information Processing Systems 33, 2020 | 18 | 2020 |
| Novel mechanisms for online crowdsourcing with unreliable, strategic agents P Chandra, Y Narahari, D Mandal, P Dey AAAI'15 Twenty-Ninth AAAI Conference on Artificial Intelligence, 1256-1262, 2015 | 18 | 2015 |
| Corruption robust offline reinforcement learning with human feedback D Mandal, A Nika, P Kamalaruban, A Singla, G Radanović International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 | 15 | 2024 |
| Feature-based individual fairness in k-clustering D Kar, M Kosan, D Mandal, S Medya, A Silva, P Dey, S Sanyal arXiv preprint arXiv:2109.04554, 2021 | 14 | 2021 |
| Implicit poisoning attacks in two-agent reinforcement learning: Adversarial policies for training-time attacks M Mohammadi, J Nöther, D Mandal, A Singla, G Radanovic arXiv preprint arXiv:2302.13851, 2023 | 13 | 2023 |
| The Effectiveness of Peer Prediction in Long-Term Forecasting M Debmalya, R Goran, P David Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 2160-2167, 2020 | 10 | 2020 |
| Online reinforcement learning with uncertain episode lengths D Mandal, G Radanovic, J Gan, A Singla, R Majumdar Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 9064-9071, 2023 | 9 | 2023 |
| Performative reinforcement learning in gradually shifting environments B Rank, S Triantafyllou, D Mandal, G Radanovic Uncertainty in Artificial Intelligence (UAI), 2024 | 8 | 2024 |
Goran RadanovićResearch Group Leader, Max Planck Institute for Software SystemsVerified email at mpi-sws.org
