 Monotonicity Testing of High-Dimensional Distributions with Subcube ConditioningSymposium on the Theory of Computing (STOC), 2025 |
 Model Stealing for Any Low-Rank Language ModelSymposium on the Theory of Computing (STOC), 2024 |
 Testing properties of distributions in the streaming modelInternational Symposium on Algorithms and Computation (ISAAC), 2023 |
 Lifting uniform learners via distributional decompositionSymposium on the Theory of Computing (STOC), 2023 |
 Learning Hidden Markov Models Using Conditional SamplesAnnual Conference Computational Learning Theory (COLT), 2023 |
 Uniformity Testing over Hypergrids with Subcube ConditioningACM-SIAM Symposium on Discrete Algorithms (SODA), 2023 |
 Complexity of High-Dimensional Identity Testing with Coordinate
Conditional SamplingAnnual Conference Computational Learning Theory (COLT), 2022 |
 A Scalable Shannon Entropy EstimatorInternational Conference on Computer Aided Verification (CAV), 2022 |
 On Distribution Testing in the Conditional Sampling ModelACM-SIAM Symposium on Discrete Algorithms (SODA), 2020 |
 Learning and Testing Junta Distributions with Subcube ConditioningAnnual Conference Computational Learning Theory (COLT), 2020 |
 Efficient Distance Approximation for Structured High-Dimensional
Distributions via LearningNeural Information Processing Systems (NeurIPS), 2020 |
 Faster Sublinear Algorithms using Conditional SamplingACM-SIAM Symposium on Discrete Algorithms (SODA), 2016 |
 Testing Shape Restrictions of Discrete DistributionsTheory of Computing Systems (TCS), 2015 |
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 A Chasm Between Identity and Equivalence Testing with Conditional
QueriesInternational Workshop and International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM), 2014 |
 Testing probability distributions underlying aggregated dataInternational Colloquium on Automata, Languages and Programming (ICALP), 2014 |
