Shiragur, Kirankumar

19 publications

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

ICML 2025 Sort Before You Prune: Improved Worst-Case Guarantees of the DiskANN Family of Graphs Siddharth Gollapudi, Ravishankar Krishnaswamy, Kirankumar Shiragur, Harsh Wardhan

TMLR 2025 Testing with Non-Identically Distributed Samples Shivam Garg, Chirag Pabbaraju, Kirankumar Shiragur, Gregory Valiant

AISTATS 2024 Causal Discovery Under Off-Target Interventions Davin Choo, Kirankumar Shiragur, Caroline Uhler

ICML 2024 Causal Discovery with Fewer Conditional Independence Tests Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler

NeurIPS 2024 Learning Mixtures of Unknown Causal Interventions Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler

AISTATS 2024 Membership Testing in Markov Equivalence Classes via Independence Queries Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler

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

UAI 2023 Adaptivity Complexity for Causal Graph Discovery Davin Choo, Kirankumar Shiragur

NeurIPS 2023 Meek Separators and Their Applications in Targeted Causal Discovery Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler

ICML 2023 New Metrics and Search Algorithms for Weighted Causal DAGs Davin Choo, Kirankumar Shiragur

NeurIPS 2023 Structured Semidefinite Programming for Recovering Structured Preconditioners Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian

AISTATS 2023 Subset Verification and Search Algorithms for Causal DAGs Davin Choo, Kirankumar Shiragur

NeurIPS 2022 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

ICML 2021 Reward Identification in Inverse Reinforcement Learning Kuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon

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

NeurIPS 2020 Instance Based Approximations to Profile Maximum Likelihood Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford

NeurIPS 2019 A General Framework for Symmetric Property Estimation Moses Charikar, Kirankumar Shiragur, Aaron Sidford