Chenglin Fan

Seoul National University — South Korea

Computer Science · Physical Sciences

7h-index182citations60works0.12yr avg
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Research Topics

Computational Geometry and Mesh Generation(25), Data Management and Algorithms(22), Complexity and Algorithms in Graphs(10), Advanced Graph Theory Research(7), Privacy-Preserving Technologies in Data(6)

Publications60 total

1.64-Approximation for Chromatic Correlation Clustering via Chromatic Cluster LP
ArXiv.org·2025Open Access
Learning Augmented Graph $k$-Clustering
arXiv (Cornell University)·2025Open Access
EALG: Evolutionary Adversarial Generation of Language Model-Guided Generators for Combinatorial Optimization
arXiv (Cornell University)·2025Open Access
Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering
arXiv (Cornell University)·2025Open Access
A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances
arXiv (Cornell University)·2025Open Access
Fitting Metrics and Ultrametrics with Minimum Disagreements
SIAM Journal on Computing·2025
Linear Expected Complexity for Directional and Multiplicative Voronoi Diagrams
Discrete & Computational Geometry·2024· 1 cited
A PTAS for <i>ℓ</i><sub>0</sub>-Low Rank Approximation: Solving Dense CSPs over Reals
Society for Industrial and Applied Mathematics eBooks·2024
A PTAS for $\ell_0$-Low Rank Approximation: Solving Dense CSPs over Reals
arXiv (Cornell University)·2023Open Access
Faster Algorithms for Generalized Mean Densest Subgraph Problem
arXiv (Cornell University)·2023Open Access
Fréchet Distance for Uncertain Curves
ACM Transactions on Algorithms·2023· 6 citedOpen Access
Metric Nearness with Minimum Distortion: Optimal and Approximation
2022 IEEE Information Theory Workshop (ITW)·2022
Fitting Metrics and Ultrametrics with Minimum Disagreements
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)·2022· 3 cited
Fitting Metrics and Ultrametrics with Minimum Disagreements
arXiv (Cornell University)·2022Open Access
Distances Release with Differential Privacy in Tree and Grid Graph
2022 IEEE International Symposium on Information Theory (ISIT)·2022· 7 cited
$k$-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
arXiv (Cornell University)·2022· 1 citedOpen Access
Breaking the Linear Error Barrier in Differentially Private Graph Distance Release
arXiv (Cornell University)·2022· 3 citedOpen Access
Distances Release with Differential Privacy in Tree and Grid Graph
arXiv (Cornell University)·2022Open Access
Near-Optimal Correlation Clustering with Privacy
arXiv (Cornell University)·2022· 3 citedOpen Access
Metric Violation Distance: Hardness and Approximation
Algorithmica·2022· 1 cited
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Frequent Co-authors

Binhai Zhu(16), Benjamin Raichel(10), Jun Luo(8), Gregory Van Buskirk(5), Jinfei Liu(5), Jun Luo(5), Farong Zhong(5), Vincent Cohen-Addad(4), Wenqi Ju(3), Jun Luo(3), Jun Luo(3), Wencheng Wang(3), Euiwoong Lee(3), Arnaud de Mesmay(3), Omrit Filtser(3), Matthew J. Katz(3), Ovidiu Daescu(2), Juncheng Yang(2), Li Xiong(2), Jian Pei(2)