Graph kernels have become an established and widely-used technique for solving
classification tasks on graphs. This survey gives a comprehensive overview of techniques …

Semidefinite programs are convex optimization problems involving a linear objective
function and a domain of positive-semidefinite matrices. Over the past two decades, they …

Self-testing is a method to infer the underlying physics of a quantum experiment in a black
box scenario. As such it represents the strongest form of certification for quantum systems. In …

A central result in the foundations of quantum mechanics is the Kochen-Specker theorem. In
short, it states that quantum mechanics is in conflict with classical models in which the result …

Quantum information processing exploits the quantum nature of information. It offers
fundamentally new solutions in the field of computer science and extends the possibilities to …

This book gives an elementary treatment of the basic material about graph spectra, both for
ordinary, and Laplace and Seidel spectra. The text progresses systematically, by covering …

Every branch of mathematics employs some notion of a product that enables the com-
bination or decomposition of its elemental structures. In graph theory there are four main …

In this article, we have provided general, comprehensive coverage of the SDR technique,
from its practical deployments and scope of applicability to key theoretical results. We have …

We propose an analytical framework for studying parallel repetition, a basic product
operation for one-round twoplayer games. In this framework, we consider a relaxation of the …

The formalism of probabilistic graphical models provides a unifying framework for capturing
complex dependencies among random variables, and building large-scale multivariate …