Counting and enumeration of local topological structures, such as triangles, is an important
task for analyzing large real‐life networks. For instance, triangle count in a network is used …

Over the last decade, there has been considerable interest in designing algorithms for
processing massive graphs in the data stream model. The original motivation was two-fold …

We study the problem of estimating the trace of a matrix A that can only be accessed through
matrix-vector multiplication. We introduce a new randomized algorithm, Hutch++, which …

We develop new methods based on graph motifs for graph clustering, allowing more
efficient detection of communities within networks. We focus on triangles within graphs, but …

Efficient join processing is one of the most fundamental and well-studied tasks in database
research. In this work, we examine algorithms for natural join queries over many relations …

Numerous graph mining applications rely on detecting subgraphs which are large near-
cliques. Since formulations that are geared towards finding large near-cliques are hard and …

Triangle counting and enumeration has emerged as a basic tool in large-scale network
analysis, fueling the development of algorithms that scale to massive graphs. Most of the …

This paper presents a new space-efficient algorithm for counting and sampling triangles--
and more generally, constant-sized cliques--in a massive graph whose edges arrive as a …

“Ogni lassada xe persa.” 1--Proverb from Trieste, Italy. We present trièst, a suite of one-pass
streaming algorithms to compute unbiased, low-variance, high-quality approximations of the …

We consider the problem of estimating the number of triangles in a graph. This problem has
been extensively studied in both theory and practice, but all existing algorithms read the …