11 citations · 23 across the 14 of their papers we have counts for
8 papers · 1 filter
DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering
Shangdi Yu, Laxman Dhulipala, Jakub Łącki +1
We consider the problem of maintaining a hierarchical agglomerative clustering (HAC) in the dynamic setting, when the input is subject to point insertions and deletions. We introdu…
Approximate Nearest Neighbor Search with Window Filters
Joshua Engels, Benjamin Landrum, Shangdi Yu +2
We define and investigate the problem of : approximate nearest neighbor search where each point in the dataset has a numeric label, and the go…
PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search
Shangdi Yu, Joshua Engels, Yihao Huang +1
This paper studies density-based clustering of point sets. These methods use dense regions of points to detect clusters of arbitrary shapes. In particular, we study variants of den…
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…
ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
Shangdi Yu, Yiqiu Wang, Yan Gu +2
This paper studies the hierarchical clustering problem, where the goal is to produce a dendrogram that represents clusters at varying scales of a data set. We propose the ParChain…
Parallel Batch-Dynamic Algorithms for -Core Decomposition and Related Graph Problems
Quanquan C. Liu, Jessica Shi, Shangdi Yu +2
Maintaining a -core decomposition quickly in a dynamic graph has important applications in network analysis. The main challenge for designing efficient exact algorithms is that…
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…
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…