The possibility to simulate the properties of many-body open quantum systems with a large
number of degrees of freedom (dof) is the premise to the solution of several outstanding …

Excerpt More than 25 years have passed since the first edition of this book was published in
1996. Least squares and least-norm problems have become more significant with every …

This is an elementary introduction to the Hodge Laplacian on a graph, a higher-order
generalization of the graph Laplacian. We will discuss basic properties including …

An iterative method LSMR is presented for solving linear systems Ax=b and least-squares
problems \min‖Ax-b‖_2, with A being sparse or a fast linear operator. LSMR is based on …

Tasks in multi-task learning often correlate, conflict, or even compete with each other. As a
result, a single solution that is optimal for all tasks rarely exists. Recent papers introduced …

Perturbative and non-perturbative expansion methods already constitute a tool of choice to
perform ab initio calculations over a significant part of the nuclear chart. In this context, the …

Imposing constraints on the output of a Deep Neural Net is one way to improve the quality of
its predictions while loosening the requirements for labeled training data. Such constraints …

We propose a technique that we call HodgeRank for ranking data that may be incomplete
and imbalanced, characteristics common in modern datasets coming from e-commerce and …

In spite of missing dynamical correlations, the projected generator coordinate method
(PGCM) was recently shown to be a suitable method to tackle the low-lying spectroscopy of …

The strategies for and the performance of the CMS silicon tracking system alignment during
the 2015–2018 data-taking period of the LHC are described. The alignment procedures …