Upward planarity testing and Rectilinear planarity testing are central
p...
Recently, Brand, Ganian and Simonov introduced a parameterized refinemen...
The fundamental theorem of Turán from Extremal Graph Theory determines
t...
Parameterization above (or below) a guarantee is a successful concept in...
Probably Approximately Correct (i.e., PAC) learning is a core concept of...
The study of fair algorithms has become mainstream in machine learning a...
The generic homomorphism problem, which asks whether an input graph G
ad...
We present an O(n^2)-time algorithm to test whether an n-vertex directed...
We introduce a general method for obtaining fixed-parameter algorithms f...
Bonnet et al. (FOCS 2020) introduced the graph invariant twin-width and
...
We obtain new parameterized algorithms for the classical problem of
dete...
In 1959, Erdős and Gallai proved that every graph G with average vertex
...
We study two "above guarantee" versions of the classical Longest Path pr...
k-means and k-median clustering are powerful unsupervised machine
learni...
In this paper, we consider the Minimum-Load k-Clustering/Facility Locati...
In this work, we study the k-median clustering problem with an additiona...
We develop new algorithmic methods with provable guarantees for feature
...
In 1952, Dirac proved the following theorem about long cycles in graphs ...
We consider a generalization of the fundamental k-means clustering for d...
Fair clustering is a constrained variant of clustering where the goal is...
A popular model to measure network stability is the k-core, that is the
...
Gerrymandering is a practice of manipulating district boundaries and
loc...
Principal component analysis (PCA) is one of the most fundamental proced...
We consider ℓ_1-Rank-r Approximation over GF(2), where for a binary
m× n...
We consider the k-Clustering problem, which is for a given multiset of n...