This paper reviews the vast literature on static output feedback design for linear time-
invariant systems including classical results and recent developments. In particular, we …

This article reviews the gradient sampling methodology for solving nonsmooth, nonconvex
optimization problems. We state an intuitively straightforward gradient sampling algorithm …

We investigate the potential of quasi-Newton methods in facilitating convergence of
monolithic solution schemes for phase field fracture modelling. Several paradigmatic …

We present a generalised phase field-based formulation for predicting fatigue crack growth
in metals. The theoretical framework aims at covering a wide range of material behaviour …

We develop a learning principle and an efficient algorithm for batch learning from logged
bandit feedback. This learning setting is ubiquitous in online systems (eg, ad placement …

This paper identifies a severe problem of the counterfactual risk estimator typically used in
batch learning from logged bandit feedback (BLBF), and proposes the use of an alternative …

We develop a learning principle and an efficient algorithm for batch learning from logged
bandit feedback. This learning setting is ubiquitous in online systems (eg, ad placement …

The interconnection between two (or more) physical systems is always accompanied by
transfer phenomena (material, energy, information) such as transport and propagation …

The preparation of this second edition of our book was triggered by a rush of fresh
developments leading to many interesting results. The text has significantly been enlarged …

Deep learning (DL) and the collocation method are merged and used to solve partial
differential equations (PDEs) describing structures' deformation. We have considered …