Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Abstract. Over the past few years, virtualization has been employed to environments ranging from densely populated cloud computing clusters to home desktop computers. Security rese...
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
Abstract--We study how to effectively integrate reinforcement learning (RL) and programming languages via adaptation-based programming, where programs can include non-deterministic...
Abstract--Machine-to-Machine (M2M), an emerging communications paradigm, is a facilitator of data flows between machines used, e.g., in mission-critical applications. Focusing in t...
Tatjana Predojev, Jesus Alonso-Zarate, Mischa Dohl...