28 citations · 59 across the 9 of their papers we have counts for
18 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…
PIM-tree: A Skew-resistant Index for Processing-in-Memory
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch +4
The performance of today's in-memory indexes is bottlenecked by the memory latency/bandwidth wall. Processing-in-memory (PIM) is an emerging approach that potentially mitigates thi…
PaC-trees: Supporting Parallel and Compressed Purely-Functional Collections
Laxman Dhulipala, Guy E. Blelloch, Yan Gu +1
Many modern programming languages are shifting toward a functional style for collection interfaces such as sets, maps, and sequences. Functional interfaces offer many advantages, i…
Scalable Community Detection via Parallel Correlation Clustering
Jessica Shi, Laxman Dhulipala, David Eisenstat +2
Graph clustering and community detection are central problems in modern data mining. The increasing need for analyzing billion-scale data calls for faster and more scalable algorit…
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time
Laxman Dhulipala, David Eisenstat, Jakub Łącki +2
We study the widely used hierarchical agglomerative clustering (HAC) algorithm on edge-weighted graphs. We define an algorithmic framework for hierarchical agglomerative graph clus…
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…