Kirankumar Shiragur
19 papers · 2019–2026 · 6 venues · across top CS/AI venues
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causal discovery
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causal graph
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profile maximum likelihood
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approximation algorithm
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markov equivalence class
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distribution estimation
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matrix approximation
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symmetric property estimation
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sample complexity
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causal dag
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causal inference
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interventional data
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conditional independence test
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graph algorithm
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symmetric property
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statistical estimation
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causal structure learning
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generalization error
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convex relaxation
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Papers
Incorporating Token Importance in Multi-Vector Retrieval
AAAI 2026
Graph-Based Algorithms for Diverse Similarity Search
ICML 2025
Sort Before You Prune: Improved Worst-Case Guarantees of the DiskANN Family of Graphs
ICML 2025
Causal Discovery under Off-Target Interventions
AISTATS 2024
Causal Discovery with Fewer Conditional Independence Tests
ICML 2024
Learning Mixtures of Unknown Causal Interventions
NeurIPS 2024
Membership Testing in Markov Equivalence Classes via Independence Queries
AISTATS 2024
Quantifying the Gain in Weak-to-Strong Generalization
NeurIPS 2024
Adaptivity Complexity for Causal Graph Discovery
UAI 2023
Meek Separators and Their Applications in Targeted Causal Discovery
NeurIPS 2023
New metrics and search algorithms for weighted causal DAGs
ICML 2023
Structured Semidefinite Programming for Recovering Structured Preconditioners
NeurIPS 2023
Subset verification and search algorithms for causal DAGs
AISTATS 2023
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood
NeurIPS 2022
Verification and search algorithms for causal DAGs
NeurIPS 2022
Reward Identification in Inverse Reinforcement Learning
ICML 2021
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood
COLT 2021
Instance Based Approximations to Profile Maximum Likelihood
NeurIPS 2020
A General Framework for Symmetric Property Estimation
NeurIPS 2019