Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
Instruction Set Simulators (ISSes) are important tools for cross-platform software development. The simulation speed is a major concern and many approaches have been proposed to i...
Lei Gao, Stefan Kraemer, Rainer Leupers, Gerd Asch...
Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...
Abstract. This paper provides a deep insight into the learning mechanisms of UCS, a learning classifier system (LCS) derived from XCS that works under a supervised learning scheme...