Learning the community structure of a large-scale graph is a fundamental...
Effective resistances are ubiquitous in graph algorithms and network
ana...
We revisit the relation between two fundamental property testing models ...
We study property testing of properties that are definable in first-orde...
We show sublinear-time algorithms for Max Cut and Max E2Lin(q) on expand...
Social networks are often modeled using signed graphs, where vertices
co...
Estimating the number of subgraphs in data streams is a fundamental prob...
The stochastic block model (SBM) is a fundamental model for studying gra...
Motivated by applications in crowdsourced entity resolution in database,...
Effective resistance is an important metric that measures the similarity...
We contribute to the theoretical understanding of randomized search
heur...
In Property Testing, proximity-oblivious testers (POTs) form a class of
...
We give two fully dynamic algorithms that maintain a
(1+ε)-approximation...
We study property testing of properties that are definable in first-orde...
For any undirected graph G=(V,E) and a set E_W of candidate edges with
E...
Spectral clustering is one of the most popular clustering methods for fi...
Dynamic optimization problems have gained significant attention in
evolu...
We present a simple sublinear-time algorithm for sampling an arbitrary
s...
With few exceptions (namely, algorithms for maximal matching, 2-approxim...
We present a novel framework closely linking the areas of property testi...
Due to the massive size of modern network data, local algorithms that ru...
Clustering is fundamental for gaining insights from complex networks, an...
One of the most fundamental questions in graph property testing is to
ch...
We consider the problem of dynamically maintaining (approximate) all-pai...
We introduce a new algorithmic framework for designing dynamic graph
alg...
We develop a new algorithmic technique that allows to transfer some cons...