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ORCIDKirankumar Shiragur
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2020 – today
- 2024
[c20]Davin Choo, Kirankumar Shiragur, Caroline Uhler:
Causal Discovery under Off-Target Interventions. AISTATS 2024: 1621-1629- [c19]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Queries. AISTATS 2024: 3925-3933 - [c18]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. ICML 2024 - [i23]Davin Choo, Kirankumar Shiragur, Caroline Uhler
:
Causal Discovery under Off-Target Interventions. CoRR abs/2402.08229 (2024) - [i22]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Query Oracles. CoRR abs/2403.05759 (2024) - [i21]Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur:
Quantifying the Gain in Weak-to-Strong Generalization. CoRR abs/2405.15116 (2024) - [i20]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. CoRR abs/2406.01823 (2024) - 2023
- [c17]Davin Choo, Kirankumar Shiragur:
Subset verification and search algorithms for causal DAGs. AISTATS 2023: 4409-4442 - [c16]Davin Choo, Kirankumar Shiragur:
New metrics and search algorithms for weighted causal DAGs. ICML 2023: 5868-5903 - [c15]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS 2023 - [c14]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. NeurIPS 2023 - [c13]Davin Choo, Kirankumar Shiragur:
Adaptivity Complexity for Causal Graph Discovery. UAI 2023: 391-402 - [i19]Davin Choo, Kirankumar Shiragur:
Subset verification and search algorithms for causal DAGs. CoRR abs/2301.03180 (2023) - [i18]Davin Choo, Kirankumar Shiragur:
New metrics and search algorithms for weighted causal DAGs. CoRR abs/2305.04445 (2023) - [i17]Davin Choo, Kirankumar Shiragur:
Adaptivity Complexity for Causal Graph Discovery. CoRR abs/2306.05781 (2023) - [i16]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR abs/2310.18265 (2023) - [i15]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. CoRR abs/2310.20075 (2023) - [i14]Shivam Garg, Chirag Pabbaraju, Kirankumar Shiragur, Gregory Valiant:
Testing with Non-identically Distributed Samples. CoRR abs/2311.11194 (2023) - 2022
- [j1]Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur:
Technical Note - Assortment Planning for Two-Sided Sequential Matching Markets. Oper. Res. 70(5): 2784-2803 (2022) - [c12]Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford:
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. NeurIPS 2022 - [c11]Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya:
Verification and search algorithms for causal DAGs. NeurIPS 2022 - [i13]Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya:
Verification and search algorithms for causal DAGs. CoRR abs/2206.15374 (2022) - [i12]Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford:
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. CoRR abs/2210.06728 (2022) - 2021
- [c10]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. COLT 2021: 93-158 - [c9]Kuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon:
Reward Identification in Inverse Reinforcement Learning. ICML 2021: 5496-5505 - [c8]Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur:
A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). ITCS 2021: 85:1-85:2 - [c7]Yanjun Han, Kirankumar Shiragur:
On the Competitive Analysis and High Accuracy Optimality of Profile Maximum Likelihood. SODA 2021: 1317-1336 - [c6]Yeganeh Alimohammadi, Nima Anari, Kirankumar Shiragur, Thuy-Duong Vuong:
Fractionally log-concave and sector-stable polynomials: counting planar matchings and more. STOC 2021: 433-446 - [i11]Yeganeh Alimohammadi, Nima Anari, Kirankumar Shiragur, Thuy-Duong Vuong:
Fractionally Log-Concave and Sector-Stable Polynomials: Counting Planar Matchings and More. CoRR abs/2102.02708 (2021) - 2020
- [c5]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Instance Based Approximations to Profile Maximum Likelihood. NeurIPS 2020 - [c4]Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur:
Assortment Planning for Two-Sided Sequential Matching Markets. WINE 2020: 475 - [i10]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
A General Framework for Symmetric Property Estimation. CoRR abs/2003.00844 (2020) - [i9]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. CoRR abs/2004.02425 (2020) - [i8]Yanjun Han, Kirankumar Shiragur:
The Optimality of Profile Maximum Likelihood in Estimating Sorted Discrete Distributions. CoRR abs/2004.03166 (2020) - [i7]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Instance Based Approximations to Profile Maximum Likelihood. CoRR abs/2011.02761 (2020) - [i6]Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur:
A Model for Ant Trail Formation and its Convergence Properties. CoRR abs/2011.14722 (2020)
2010 – 2019
- 2019
- [c3]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
A General Framework for Symmetric Property Estimation. NeurIPS 2019: 12426-12436 - [c2]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Efficient profile maximum likelihood for universal symmetric property estimation. STOC 2019: 780-791 - [i5]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation. CoRR abs/1905.08448 (2019) - [i4]Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur:
Assortment planning for two-sided sequential matching markets. CoRR abs/1907.04485 (2019) - 2018
- [i3]Arun Jambulapati, Kirankumar Shiragur, Aaron Sidford:
Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric M-Matrices. CoRR abs/1812.06295 (2018) - 2016
- [i2]Deeparnab Chakrabarty, Kirankumar Shiragur:
Graph Balancing with Two Edge Types. CoRR abs/1604.06918 (2016) - 2015
- [c1]Arnab Bhattacharyya, Kirankumar Shiragur:
How friends and non-determinism affect opinion dynamics. CDC 2015: 6466-6471 - [i1]Arnab Bhattacharyya, Kirankumar Shiragur:
How friends and non-determinism affect opinion dynamics. CoRR abs/1503.01720 (2015)
Coauthor Index
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