Jinhui Xu

Fully-Scalable Massively Parallel Algorithm for k-center with Outliers AAAI 2025 Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization AAAI 2025 Nearly Optimal Differentially Private ReLU Regression UAI 2025 New Algorithms for the Learning-Augmented k-means Problem ICLR 2025 TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram ICLR 2025 Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model ICLR 2024 Linear Time Approximation Algorithm for Column Subset Selection with Local Search NeurIPS 2024 Near-Linear Time Approximation Algorithms for k-means with Outliers ICML 2024 Revisiting Differentially Private ReLU Regression NeurIPS 2024 SEC: More Accurate Clustering Algorithm via Structural Entropy AAAI 2024 Truthful High Dimensional Sparse Linear Regression NeurIPS 2024 Understanding Forgetting in Continual Learning with Linear Regression ICML 2024 Fast Algorithms for Distributed k-Clustering with Outliers ICML 2023 Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data JMLR 2023 Linear Time Algorithms for k-means with Multi-Swap Local Search NeurIPS 2023 Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning ICLR 2023 Shifted Diffusion for Text-to-Image Generation CVPR 2023 Few-shot Learning via Dirichlet Tessellation Ensemble ICLR 2022 FLS: A New Local Search Algorithm for K-means with Smaller Search Space IJCAI 2022 On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data ACML 2022 TiGAN: Text-Based Interactive Image Generation and Manipulation AAAI 2022 Towards Language-Free Training for Text-to-Image Generation CVPR 2022 Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data ALT 2021 Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimization UAI 2021 Meta-Learning with Neural Tangent Kernels ICLR 2021 Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy JMLR 2020 Estimating Stochastic Linear Combination of Non-Linear Regressions AAAI 2020 Learning Manifold Implicitly via Explicit Heat-Kernel Learning NeurIPS 2020 On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data ICML 2020 Pairwise Learning with Differential Privacy Guarantees AAAI 2020 Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019 Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View AAAI 2019 Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation IJCAI 2019 Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations ALT 2019 On Sparse Linear Regression in the Local Differential Privacy Model ICML 2019 Principal Component Analysis in the Local Differential Privacy Model IJCAI 2019 Privacy-aware Synthesizing for Crowdsourced Data IJCAI 2019 Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited NeurIPS 2018 Differentially Private Empirical Risk Minimization Revisited: Faster and More General NeurIPS 2017 Gauging Association Patterns of Chromosome Territories via Chromatic Median CVPR 2013 k-Prototype Learning for 3D Rigid Structures NeurIPS 2013 Ensemble Clustering using Semidefinite Programming NeurIPS 2007