112 citations · 370 across the 54 of their papers we have counts for
13 papers · 1 filter
Towards Scalable and Practical Batch-Dynamic Connectivity
Quinten De Man, Laxman Dhulipala, Adam Karczmarz +3
We study the problem of dynamically maintaining the connected components of an undirected graph subject to edge insertions and deletions. We give the first parallel algorithm for t…
The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering
Shangdi Yu, Jessica Shi, Jamison Meindl +7
We introduce the ParClusterers Benchmark Suite (PCBS) -- a collection of highly scalable parallel graph clustering algorithms and benchmarking tools that streamline comparing diffe…
Results of the Big ANN: NeurIPS'23 competition
Harsha Vardhan Simhadri, Martin Aumüller, Amir Ingber +20
The 2023 Big ANN Challenge, held at NeurIPS 2023, focused on advancing the state-of-the-art in indexing data structures and search algorithms for practical variants of Approximate…
Parallel Set Cover and Hypergraph Matching via Uniform Random Sampling
Laxman Dhulipala, Michael Dinitz, Jakub Łącki +1
The SetCover problem has been extensively studied in many different models of computation, including parallel and distributed settings. From an approximation point of view, there a…
Efficient Centroid-Linkage Clustering
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher +4
We give an efficient algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a -approximate clustering in roughly time. We ob…
BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers
Brian Wheatman, Xiaojun Dong, Zheqi Shen +4
A fundamental building block in any graph algorithm is a graph container - a data structure used to represent the graph. Ideally, a graph container enables efficient access to the…
Optimal Parallel Algorithms for Dendrogram Computation and Single-Linkage Clustering
Laxman Dhulipala, Xiaojun Dong, Kishen N Gowda +1
Computing a Single-Linkage Dendrogram (SLD) is a key step in the classic single-linkage hierarchical clustering algorithm. Given an input edge-weighted tree , the SLD of is…
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings
Laxman Dhulipala, Majid Hadian, Rajesh Jayaram +2
Neural embedding models have become a fundamental component of modern information retrieval (IR) pipelines. These models produce a single embedding per data-po…
It's Hard to HAC with Average Linkage!
MohammadHossein Bateni, Laxman Dhulipala, Kishen N Gowda +3
Average linkage Hierarchical Agglomerative Clustering (HAC) is an extensively studied and applied method for hierarchical clustering. Recent applications to massive datasets have d…
Fine-Grained Privacy Guarantees for Coverage Problems
Laxman Dhulipala, George Z. Li
We introduce a new notion of neighboring databases for coverage problems such as Max Cover and Set Cover under differential privacy. In contrast to the standard privacy notion for…
Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search
Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram +1
We consider the fundamental problem of decomposing a large-scale approximate nearest neighbor search (ANNS) problem into smaller sub-problems. The goal is to partition the input po…
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…
Parallel Integer Sort: Theory and Practice
Xiaojun Dong, Laxman Dhulipala, Yan Gu +1
Integer sorting is a fundamental problem in computer science. This paper studies parallel integer sort both in theory and in practice. In theory, we show tighter bounds for a class…