Kirankumar Shiragur

58 papers A* 18A 5Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents. CoRR Naman Gupta, Vaibhav Singh, Arun Iyer, Kirankumar Shiragur, Pratham Grover, Ramakrishna B. Bairi, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta, Rishikesh Maurya, Vageesh D. C.
2026	A*	`conf`	Incorporating Token Importance in Multi-Vector Retrieval. AAAI Archish S, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal
2026	J	`jnl`	On Strengths and Limitations of Single-Vector Embeddings. CoRR Archish S, Mihir Agarwal, Ankit Garg, Neeraj Kayal, Kirankumar Shiragur
2026	J	`jnl`	Welfarist Formulations for Diverse Similarity Search. CoRR Siddharth Barman, Nirjhar Das, Shivam Gupta, Kirankumar Shiragur
2025	J	`jnl`	COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context. CoRR Naman Gupta, Shreeyash Gowaikar, Arun Iyer, Kirankumar Shiragur, Ramakrishna B. Bairi, Rishikesh Maurya, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta
2025	J	`jnl`	Cost Efficient Fairness Audit Under Partial Feedback. CoRR Nirjhar Das, Mohit Sharma, Praharsh Nanavati, Kirankumar Shiragur, Amit Deshpande
2025	A*	`conf`	Graph-Based Algorithms for Diverse Similarity Search. ICML Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy, Sepideh Mahabadi, Vikas C. Raykar, Kirankumar Shiragur, Haike Xu
2025	J	`jnl`	Graph-Based Algorithms for Diverse Similarity Search. CoRR Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy, Sepideh Mahabadi, Vikas C. Raykar, Kirankumar Shiragur, Haike Xu
2025	J	`jnl`	Incorporating Token Importance in Multi-Vector Retrieval. CoRR Archish S, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal
2025	A*	`conf`	Sort Before You Prune: Improved Worst-Case Guarantees of the DiskANN Family of Graphs. ICML Siddharth Gollapudi, Ravishankar Krishnaswamy, Kirankumar Shiragur, Harsh Wardhan
2025	J	`jnl`	Testing with Non-identically Distributed Samples. Trans. Mach. Learn. Res. Shivam Garg, Chirag Pabbaraju, Kirankumar Shiragur, Gregory Valiant
2024	A	`conf`	Causal Discovery under Off-Target Interventions. AISTATS Davin Choo, Kirankumar Shiragur, Caroline Uhler
2024	J	`jnl`	Causal Discovery under Off-Target Interventions. CoRR Davin Choo, Kirankumar Shiragur, Caroline Uhler
2024	A*	`conf`	Causal Discovery with Fewer Conditional Independence Tests. ICML Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
2024	J	`jnl`	Causal Discovery with Fewer Conditional Independence Tests. CoRR Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
2024	A*	`conf`	Learning Mixtures of Unknown Causal Interventions. NeurIPS Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler
2024	J	`jnl`	Learning Mixtures of Unknown Causal Interventions. CoRR Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler
2024	A	`conf`	Membership Testing in Markov Equivalence Classes via Independence Queries. AISTATS Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler
2024	J	`jnl`	Membership Testing in Markov Equivalence Classes via Independence Query Oracles. CoRR Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler
2024	A*	`conf`	Quantifying the Gain in Weak-to-Strong Generalization. NeurIPS Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur
2024	J	`jnl`	Quantifying the Gain in Weak-to-Strong Generalization. CoRR Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur
2023	A	`conf`	Adaptivity Complexity for Causal Graph Discovery. UAI Davin Choo, Kirankumar Shiragur
2023	J	`jnl`	Adaptivity Complexity for Causal Graph Discovery. CoRR Davin Choo, Kirankumar Shiragur
2023	A*	`conf`	Meek Separators and Their Applications in Targeted Causal Discovery. NeurIPS Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
2023	J	`jnl`	Meek Separators and Their Applications in Targeted Causal Discovery. CoRR Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
2023	A*	`conf`	New metrics and search algorithms for weighted causal DAGs. ICML Davin Choo, Kirankumar Shiragur
2023	J	`jnl`	New metrics and search algorithms for weighted causal DAGs. CoRR Davin Choo, Kirankumar Shiragur
2023	A*	`conf`	Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	J	`jnl`	Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	A	`conf`	Subset verification and search algorithms for causal DAGs. AISTATS Davin Choo, Kirankumar Shiragur
2023	J	`jnl`	Subset verification and search algorithms for causal DAGs. CoRR Davin Choo, Kirankumar Shiragur
2023	J	`jnl`	Testing with Non-identically Distributed Samples. CoRR Shivam Garg, Chirag Pabbaraju, Kirankumar Shiragur, Gregory Valiant
2022	A*	`conf`	On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. NeurIPS Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford
2022	J	`jnl`	On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. CoRR Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford
2022	J	`jnl`	Technical Note - Assortment Planning for Two-Sided Sequential Matching Markets. Oper. Res. Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur
2022	A*	`conf`	Verification and search algorithms for causal DAGs. NeurIPS Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya
2022	J	`jnl`	Verification and search algorithms for causal DAGs. CoRR Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya
2021	A	`conf`	A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). ITCS Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur
2021	J	`jnl`	Fractionally Log-Concave and Sector-Stable Polynomials: Counting Planar Matchings and More. CoRR Yeganeh Alimohammadi, Nima Anari, Kirankumar Shiragur, Thuy-Duong Vuong
2021	A*	`conf`	Fractionally log-concave and sector-stable polynomials: counting planar matchings and more. STOC Yeganeh Alimohammadi, Nima Anari, Kirankumar Shiragur, Thuy-Duong Vuong
2021	A*	`conf`	On the Competitive Analysis and High Accuracy Optimality of Profile Maximum Likelihood. SODA Yanjun Han, Kirankumar Shiragur
2021	A*	`conf`	Reward Identification in Inverse Reinforcement Learning. ICML Kuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon
2021	A*	`conf`	The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. COLT Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2020	J	`jnl`	A General Framework for Symmetric Property Estimation. CoRR Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2020	J	`jnl`	A Model for Ant Trail Formation and its Convergence Properties. CoRR Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur
2020	—	`conf`	Assortment Planning for Two-Sided Sequential Matching Markets. WINE Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur
2020	A*	`conf`	Instance Based Approximations to Profile Maximum Likelihood. NeurIPS Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2020	J	`jnl`	Instance Based Approximations to Profile Maximum Likelihood. CoRR Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2020	J	`jnl`	The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. CoRR Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2020	J	`jnl`	The Optimality of Profile Maximum Likelihood in Estimating Sorted Discrete Distributions. CoRR Yanjun Han, Kirankumar Shiragur
2019	A*	`conf`	A General Framework for Symmetric Property Estimation. NeurIPS Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2019	J	`jnl`	Assortment planning for two-sided sequential matching markets. CoRR Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani, Daniela Sabán, Kirankumar Shiragur
2019	J	`jnl`	Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation. CoRR Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2019	A*	`conf`	Efficient profile maximum likelihood for universal symmetric property estimation. STOC Moses Charikar, Kirankumar Shiragur, Aaron Sidford
2018	J	`jnl`	Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric M-Matrices. CoRR Arun Jambulapati, Kirankumar Shiragur, Aaron Sidford
2016	J	`jnl`	Graph Balancing with Two Edge Types. CoRR Deeparnab Chakrabarty, Kirankumar Shiragur
2015	—	`conf`	How friends and non-determinism affect opinion dynamics. CDC Arnab Bhattacharyya, Kirankumar Shiragur
2015	J	`jnl`	How friends and non-determinism affect opinion dynamics. CoRR Arnab Bhattacharyya, Kirankumar Shiragur