| Finding fair and efficient allocations S Barman, SK Krishnamurthy, R Vaish Proceedings of the 2018 ACM Conference on Economics and Computation, 557-574, 2018 | 274 | 2018 |
| Approximation algorithms for maximin fair division S Barman, SK Krishnamurthy ACM Transactions on Economics and Computation (TEAC) 8 (1), 1-28, 2020 | 196 | 2020 |
| Greedy algorithms for maximizing Nash social welfare S Barman, SK Krishnamurthy, R Vaish arXiv preprint arXiv:1801.09046, 2018 | 95 | 2018 |
| Groupwise maximin fair allocation of indivisible goods S Barman, A Biswas, S Krishnamurthy, Y Narahari Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 79 | 2018 |
| On the proximity of markets with integral equilibria S Barman, SK Krishnamurthy Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1748-1755, 2019 | 64 | 2019 |
| Adapting to misspecification in contextual bandits with offline regression oracles SK Krishnamurthy, V Hadad, S Athey International Conference on Machine Learning, 5805-5814, 2021 | 28 | 2021 |
| Contextual bandits in a survey experiment on charitable giving: Within-experiment outcomes versus policy learning S Athey, U Byambadalai, V Hadad, SK Krishnamurthy, W Leung, ... arXiv preprint arXiv:2211.12004, 2022 | 16 | 2022 |
| Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective SK Krishnamurthy, A Margaret Propp, S Athey International Conference on Artificial Intelligence and Statistics, 2476-2484, 2024 | 15* | 2024 |
| Tractable contextual bandits beyond realizability SK Krishnamurthy, V Hadad, S Athey International Conference on Artificial Intelligence and Statistics, 1423-1431, 2021 | 15 | 2021 |
| Flexible and efficient contextual bandits with heterogeneous treatment effect oracles AG Carranza, SK Krishnamurthy, S Athey International Conference on Artificial Intelligence and Statistics, 7190-7212, 2023 | 13 | 2023 |
| Proportional response: Contextual bandits for simple and cumulative regret minimization SK Krishnamurthy, R Zhan, S Athey, E Brunskill Advances in Neural Information Processing Systems 36, 30255-30266, 2023 | 10 | 2023 |
| Survey bandits with regret guarantees SK Krishnamurthy, S Athey arXiv preprint arXiv:2002.09814, 2020 | 5 | 2020 |
| Data-driven Error Estimation: Upper Bounding Multiple Errors with No Technical Debt SK Krishnamurthy, S Athey, E Brunskill arXiv preprint arXiv:2405.04636, 2024 | 1 | 2024 |
| Selective Uncertainty Propagation in Offline RL SK Krishnamurthy, T Gangwani, S Katariya, B Kveton, A Rangi arXiv preprint arXiv:2302.00284, 2023 | 1 | 2023 |
| Rethinking Uncertainty Quantification for Contextual Bandits SK Krishnamurthy Stanford University, 2024 | | 2024 |
Siddharth BarmanDepartment of Computer Science and Automation, IISciisc.ac.in의 이메일 확인됨