How friends and non-determinism affect opinion dynamics. - Arnab Bhattacharyya 001; Kirankumar Shiragur (CDC, 2015)

Graph Balancing with Two Edge Types. - Deeparnab Chakrabarty; Kirankumar Shiragur (CoRR, 2016)

Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric M-Matrices. - Arun Jambulapati; Kirankumar Shiragur; Aaron Sidford (CoRR, 2018)

A General Framework for Symmetric Property Estimation. - Moses Charikar; Kirankumar Shiragur; Aaron Sidford (NeurIPS, 2019)

Efficient profile maximum likelihood for universal symmetric property estimation. - Moses Charikar; Kirankumar Shiragur; Aaron Sidford (STOC, 2019)

Instance Based Approximations to Profile Maximum Likelihood. - Nima Anari; Moses Charikar; Kirankumar Shiragur; Aaron Sidford (NeurIPS, 2020)

Assortment Planning for Two-Sided Sequential Matching Markets. - Itai Ashlagi; Anilesh K. Krishnaswamy; Rahul Makhijani; Daniela Sabán; Kirankumar Shiragur (WINE, 2020)

The Optimality of Profile Maximum Likelihood in Estimating Sorted Discrete Distributions. - Yanjun Han; Kirankumar Shiragur (CoRR, 2020)

A Model for Ant Trail Formation and its Convergence Properties. - Moses Charikar; Shivam Garg 001; Deborah M. Gordon; Kirankumar Shiragur (CoRR, 2020)

The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. - Nima Anari; Moses Charikar; Kirankumar Shiragur; Aaron Sidford (COLT, 2021)

Reward Identification in Inverse Reinforcement Learning. - Kuno Kim; Shivam Garg 001; Kirankumar Shiragur; Stefano Ermon (ICML, 2021)

A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). - Moses Charikar; Shivam Garg 001; Deborah M. Gordon; Kirankumar Shiragur (ITCS, 2021)

On the Competitive Analysis and High Accuracy Optimality of Profile Maximum Likelihood. - Yanjun Han; Kirankumar Shiragur (SODA, 2021)

Fractionally log-concave and sector-stable polynomials: counting planar matchings and more. - Yeganeh Alimohammadi; Nima Anari; Kirankumar Shiragur; Thuy-Duong Vuong (STOC, 2021)

On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. - Moses Charikar; Zhihao Jiang; Kirankumar Shiragur; Aaron Sidford (NeurIPS, 2022)

Verification and search algorithms for causal DAGs. - Davin Choo; Kirankumar Shiragur; Arnab Bhattacharyya 001 (NeurIPS, 2022)

Technical Note - Assortment Planning for Two-Sided Sequential Matching Markets. - Itai Ashlagi; Anilesh K. Krishnaswamy; Rahul Makhijani; Daniela Sabán; Kirankumar Shiragur (Oper. Res., 2022)

Subset verification and search algorithms for causal DAGs. - Davin Choo; Kirankumar Shiragur (AISTATS, 2023)

New metrics and search algorithms for weighted causal DAGs. - Davin Choo; Kirankumar Shiragur (ICML, 2023)

Structured Semidefinite Programming for Recovering Structured Preconditioners. - Arun Jambulapati; Jerry Li 001; Christopher Musco; Kirankumar Shiragur; Aaron Sidford; Kevin Tian (NeurIPS, 2023)

Meek Separators and Their Applications in Targeted Causal Discovery. - Kirankumar Shiragur; Jiaqi Zhang; Caroline Uhler (NeurIPS, 2023)

Adaptivity Complexity for Causal Graph Discovery. - Davin Choo; Kirankumar Shiragur (UAI, 2023)

Testing with Non-identically Distributed Samples. - Shivam Garg 001; Chirag Pabbaraju; Kirankumar Shiragur; Gregory Valiant (CoRR, 2023)

Causal Discovery under Off-Target Interventions. - Davin Choo; Kirankumar Shiragur; Caroline Uhler (AISTATS, 2024)

Membership Testing in Markov Equivalence Classes via Independence Queries. - Jiaqi Zhang; Kirankumar Shiragur; Caroline Uhler (AISTATS, 2024)

Causal Discovery with Fewer Conditional Independence Tests. - Kirankumar Shiragur; Jiaqi Zhang; Caroline Uhler (ICML, 2024)

Quantifying the Gain in Weak-to-Strong Generalization. - Moses Charikar; Chirag Pabbaraju; Kirankumar Shiragur (NeurIPS, 2024)

Learning Mixtures of Unknown Causal Interventions. - Abhinav Kumar; Kirankumar Shiragur; Caroline Uhler (NeurIPS, 2024)

Membership Testing in Markov Equivalence Classes via Independence Query Oracles. - Jiaqi Zhang; Kirankumar Shiragur; Caroline Uhler (CoRR, 2024)

Graph-Based Algorithms for Diverse Similarity Search. - Piyush Anand; Piotr Indyk; Ravishankar Krishnaswamy; Sepideh Mahabadi; Vikas C. Raykar; Kirankumar Shiragur; Haike Xu (CoRR, 2025)