Local majorities, coalitions and monopolies in graphs: a review Page 1 Theoretical Computer
Science 282 (2002) 231–257 www.elsevier.com/locate/tcs Local majorities, coalitions and …

Graph neural networks (GNNs) are powerful machine learning models for various graph
learning tasks. Recently, the limitations of the expressive power of various GNN models …

The local ratio technique is a methodology for the design and analysis of algorithms for a
broad range of optimization problems. The technique is remarkably simple and elegant, and …

A comprehensive update of the leading algorithms text, with new material on matchings in
bipartite graphs, online algorithms, machine learning, and other topics. Some books on …

Although this may seem a paradox, all exact science is dominated by the idea of
approximation. Bertrand Russell (1872-1970) Most natural optimization problems, including …

Given a collection ℱ of subsets of S={1,…, n}, set cover is the problem of selecting as few as
possible subsets from ℱ such that their union covers S,, and max k-cover is the problem of …

Let us start with two examples. A company has a machine which drills holes into printed
circuit boards. Since it produces many of these boards it wants the machine to complete one …

Let A be a binary matrix of size m× n, let cT be a positive row vector of length n and let e be
the column vector, all of whose m components are ones. The set-covering problem is to …

Graph Theory has proved to be an extremely useful tool for solving combinatorial problems
in such diverse areas as Geometry, Algebra, Number Theory, Topology, Operations …

Data mining applications place special requirements on clustering algorithms including: the
ability to find clusters embedded in subspaces of high dimensional data, scalability, end …