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Sanath Kumar Krishnamurthy
Sanath Kumar Krishnamurthy
PhD student, Stanford
Verified email at stanford.edu - Homepage
Title
Cited by
Cited by
Year
Finding fair and efficient allocations
S Barman, SK Krishnamurthy, R Vaish
Proceedings of the 2018 ACM Conference on Economics and Computation, 557-574, 2018
1762018
Approximation Algorithms for Maximin Fair Division
S Barman, SK Krishnamurthy
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017
1322017
Greedy algorithms for maximizing Nash social welfare
S Barman, SK Krishnamurthy, R Vaish
arXiv preprint arXiv:1801.09046, 2018
652018
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
602018
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
322019
Adapting to misspecification in contextual bandits with offline regression oracles
SK Krishnamurthy, V Hadad, S Athey
International Conference on Machine Learning, 5805-5814, 2021
122021
Tractable contextual bandits beyond realizability
SK Krishnamurthy, V Hadad, S Athey
International Conference on Artificial Intelligence and Statistics, 1423-1431, 2021
102021
Optimal model selection in contextual bandits with many classes via offline oracles
SK Krishnamurthy, S Athey
arXiv preprint arXiv:2106.06483, 2021
62021
Survey bandits with regret guarantees
SK Krishnamurthy, S Athey
arXiv preprint arXiv:2002.09814, 2020
42020
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracle
AG Carranza, SK Krishnamurthy, S Athey
arXiv preprint arXiv:2203.16668, 2022
32022
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
2022
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