Jinhui Xu
42 papers · 2007–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (10) πΊοΈ Taxonomy Completionist (12) π Interdisciplinary Bridge π Academic Marathon (18)
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Keyword Pioneer
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Interdisciplinary Bridge
π
Conference Polyglot
(10)
π
Grand Slam
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Deep Specialist
(17)
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Dynamic Duo
(22)
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Triple Crown
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Keyword Champion
ποΈ
Keyword Collector
(146)
β‘
Prolific Year
(7)
π
Conference Pioneer
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Trend Setter
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Century Club
(42)
π₯
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
Research topics
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