| Fractionally log-concave and sector-stable polynomials: counting planar matchings and more Y Alimohammadi, N Anari, K Shiragur, TD Vuong Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 48 | 2021 |
| Reward identification in inverse reinforcement learning K Kim, S Garg, K Shiragur, S Ermon International Conference on Machine Learning, 5496-5505, 2021 | 41 | 2021 |
| Assortment planning for two-sided sequential matching markets I Ashlagi, AK Krishnaswamy, R Makhijani, D Saban, K Shiragur Operations Research 70 (5), 2784-2803, 2022 | 32 | 2022 |
| Efficient profile maximum likelihood for universal symmetric property estimation M Charikar, K Shiragur, A Sidford Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 27 | 2019 |
| The Bethe and Sinkhorn permanents of low rank matrices and implications for profile maximum likelihood N Anari, M Charikar, K Shiragur, A Sidford Conference on Learning Theory, 93-158, 2021 | 12 | 2021 |
| Verification and search algorithms for causal DAGs D Choo, K Shiragur, A Bhattacharyya Advances in Neural Information Processing Systems 35, 12787-12799, 2022 | 11 | 2022 |
| On the competitive analysis and high accuracy optimality of profile maximum likelihood Y Han, K Shiragur Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA …, 2021 | 11 | 2021 |
| A general framework for symmetric property estimation M Charikar, K Shiragur, A Sidford Advances in neural information processing systems 32, 2019 | 10 | 2019 |
| Graph balancing with two edge types D Chakrabarty, K Shiragur arXiv preprint arXiv:1604.06918, 2016 | 9 | 2016 |
| Subset verification and search algorithms for causal DAGs D Choo, K Shiragur International Conference on Artificial Intelligence and Statistics, 4409-4442, 2023 | 8 | 2023 |
| Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric -Matrices A Jambulapati, K Shiragur, A Sidford arXiv preprint arXiv:1812.06295, 2018 | 8 | 2018 |
| Instance based approximations to profile maximum likelihood N Anari, M Charikar, K Shiragur, A Sidford Advances in neural information processing systems 33, 20272-20285, 2020 | 7 | 2020 |
| How friends and non-determinism affect opinion dynamics A Bhattacharyya, K Shiragur 2015 54th IEEE Conference on Decision and Control (CDC), 6466-6471, 2015 | 7 | 2015 |
| Distributed algorithms from arboreal ants for the shortest path problem S Garg, K Shiragur, DM Gordon, M Charikar Proceedings of the National Academy of Sciences 120 (6), e2207959120, 2023 | 6 | 2023 |
| Quantifying the Gain in Weak-to-Strong Generalization M Charikar, C Pabbaraju, K Shiragur arXiv preprint arXiv:2405.15116, 2024 | 3 | 2024 |
| Structured semidefinite programming for recovering structured preconditioners A Jambulapati, J Li, C Musco, K Shiragur, A Sidford, K Tian Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Adaptivity complexity for causal graph discovery D Choo, K Shiragur Uncertainty in Artificial Intelligence, 391-402, 2023 | 2 | 2023 |
| A Model for Ant Trail Formation and its Convergence Properties M Charikar, S Garg, DM Gordon, K Shiragur 12th Innovations in Theoretical Computer Science Conference (ITCS 2021), 2021 | 2 | 2021 |
| Membership testing in markov equivalence classes via independence queries J Zhang, K Shiragur, C Uhler International Conference on Artificial Intelligence and Statistics, 3925-3933, 2024 | 1 | 2024 |
| Meek separators and their applications in targeted causal discovery K Shiragur, J Zhang, C Uhler Advances in Neural Information Processing Systems 36, 48744-48767, 2023 | 1 | 2023 |
Moses CharikarProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
