フォロー
Sanath Kumar Krishnamurthy
Sanath Kumar Krishnamurthy
Research Scientist, Meta
確認したメール アドレス: stanford.edu - ホームページ
タイトル
引用先
引用先
Finding fair and efficient allocations
S Barman, SK Krishnamurthy, R Vaish
Proceedings of the 2018 ACM Conference on Economics and Computation, 557-574, 2018
2752018
Approximation algorithms for maximin fair division
S Barman, SK Krishnamurthy
ACM Transactions on Economics and Computation (TEAC) 8 (1), 1-28, 2020
1962020
Greedy algorithms for maximizing Nash social welfare
S Barman, SK Krishnamurthy, R Vaish
arXiv preprint arXiv:1801.09046, 2018
952018
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
792018
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
642019
Adapting to misspecification in contextual bandits with offline regression oracles
SK Krishnamurthy, V Hadad, S Athey
International Conference on Machine Learning, 5805-5814, 2021
282021
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
162022
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
152021
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
132023
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
102023
Survey bandits with regret guarantees
SK Krishnamurthy, S Athey
arXiv preprint arXiv:2002.09814, 2020
52020
Data-driven Error Estimation: Upper Bounding Multiple Errors with No Technical Debt
SK Krishnamurthy, S Athey, E Brunskill
arXiv preprint arXiv:2405.04636, 2024
12024
Selective Uncertainty Propagation in Offline RL
SK Krishnamurthy, T Gangwani, S Katariya, B Kveton, A Rangi
arXiv preprint arXiv:2302.00284, 2023
12023
Rethinking Uncertainty Quantification for Contextual Bandits
SK Krishnamurthy
Stanford University, 2024
2024
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