28 citations · 49 across the 9 of their papers we have counts for
22 papers
Differential Privacy from Locally Adjustable Graph Algorithms: -Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs
Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova +3
Differentially private algorithms allow large-scale data analytics while preserving user privacy. Designing such algorithms for graph data is gaining importance with the growth of…
Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
Yiqiu Wang, Shangdi Yu, Yan Gu +1
This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spatial clustering hierarchies (known as HDBSCAN). Our approach is based on gene…
Parallel In-Place Algorithms: Theory and Practice
Yan Gu, Omar Obeya, Julian Shun
Many parallel algorithms use at least linear auxiliary space in the size of the input to enable computations to be done independently without conflicts. Unfortunately, this extra s…
Compilation Techniques for Graph Algorithms on GPUs
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong +3
The performance of graph programs depends highly on the algorithm, the size and structure of the input graphs, as well as the features of the underlying hardware. No single set of…
Parallel Index-Based Structural Graph Clustering and Its Approximation
Tom Tseng, Laxman Dhulipala, Julian Shun
SCAN (Structural Clustering Algorithm for Networks) is a well-studied, widely used graph clustering algorithm. For large graphs, however, sequential SCAN variants are prohibitively…
A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem
Yiqiu Wang, Shangdi Yu, Yan Gu +1
We propose a theoretically-efficient and practical parallel batch-dynamic data structure for the closest pair problem. Our solution is based on a serial dynamic closest pair data s…