← Authors

Jinhui Xu

42 papers · 2007–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (18) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) πŸ† Grand Slam πŸ”¬ Deep Specialist (17) 🀝 Dynamic Duo (22) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (146) ⚑ Prolific Year (7) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (42) πŸ”₯ Unstoppable (9)

Conferences

NIPS (9) AAAI (7) ICLR (6) ICML (6) IJCAI (4) CVPR (3) ALT (2) JMLR (2) UAI (2) ACML (1)

Top co-authors

Di Wang (22) Ziyun Huang (12) Jianxin Wang (8) Qilong Feng (8) Meng Ding (7) Junyu Huang (7) Yufan Zhou (6) Changyou Chen (6) Chunwei Ma (4) Marco Gaboardi (4)

Research topics

Differential Privacy (8)

Keywords

differential privacy (10) local differential privacy (7) empirical risk minimization (6) approximation algorithm (5) sample complexity (3) combinatorial optimization (3) convex optimization (3) privacy-preserving machine learning (3) non-convex optimization (3) sub-gaussian distribution (2) generalized linear model (2) local search algorithm (2) stochastic gradient descent (2) sparse linear regression (2) gradient descent (2) clustering algorithm (2) zero-shot learning (2) text-to-image generation (2) k-means clustering (2) polynomial approximation (2)

Papers

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