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 Efficiently Computing Similarities to Private DatasetsInternational Conference on Learning Representations (ICLR), 2024 |
 Fast Private Kernel Density Estimation via Locality Sensitive
QuantizationInternational Conference on Machine Learning (ICML), 2023 |
 Differentially Private Synthetic Data Using KD-TreesConference on Uncertainty in Artificial Intelligence (UAI), 2023 |
 Dimensionality Reduction for General KDE Mode FindingInternational Conference on Machine Learning (ICML), 2023 |
 Sub-quadratic Algorithms for Kernel Matrices via Kernel Density
EstimationInternational Conference on Learning Representations (ICLR), 2022 |
 Learnware: Small Models Do BigScience China Information Sciences (Sci. China Inf. Sci.), 2022 |
 Dynamic Maintenance of Kernel Density Estimation Data Structure: From
Practice to TheoryConference on Uncertainty in Artificial Intelligence (UAI), 2022 |
 Towards Optimal Lower Bounds for k-median and k-means CoresetsSymposium on the Theory of Computing (STOC), 2022 |
 Distribution Compression in Near-linear TimeInternational Conference on Learning Representations (ICLR), 2021 |
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 A Few Interactions Improve Distributed Nonparametric Estimation,
OptimallyIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021 |
 Coresets for Classification -- Simplified and StrengthenedNeural Information Processing Systems (NeurIPS), 2021 |
 Kernel ThinningAnnual Conference Computational Learning Theory (COLT), 2021 |
 Faster Kernel Matrix Algebra via Density EstimationInternational Conference on Machine Learning (ICML), 2021 |
 Optimal Coreset for Gaussian Kernel Density EstimationInternational Symposium on Computational Geometry (SoCG), 2020 |
 Discrepancy, Coresets, and Sketches in Machine LearningAnnual Conference Computational Learning Theory (COLT), 2019 |
 Coresets for Minimum Enclosing Balls over Sliding WindowsKnowledge Discovery and Data Mining (KDD), 2019 |
