Transfer learning aims at improving the performance of target learners on target domains by
transferring the knowledge contained in different but related source domains. In this way, the …

It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

Graphs are widely used as a popular representation of the network structure of connected
data. Graph data can be found in a broad spectrum of application domains such as social …

Deep neural networks (DNN) have achieved unprecedented success in numerous machine
learning tasks in various domains. However, the existence of adversarial examples raises …

Future wireless communication systems are expected to explore spectral bands typically
used by radar systems, in order to overcome spectrum congestion of traditional …

Bell's theorem proves that quantum theory is inconsistent with local physical models. It has
propelled research in the foundations of quantum theory and quantum information science …

Graph is an important data representation which appears in a wide diversity of real-world
scenarios. Effective graph analytics provides users a deeper understanding of what is …

Although complex numbers are essential in mathematics, they are not needed to describe
physical experiments, as those are expressed in terms of probabilities, hence real numbers …

We describe a modular rewriting system for translating optimization problems written in a
domain-specific language (DSL) to forms compatible with low-level solver interfaces …

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