Abstract. Median clustering extends popular neural data analysis methods such as the self-organizing map or neural gas to general data structures given by a dissimilarity matrix on...
Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi
Self-adaptive component-based architectures facilitate the building of systems capable of dynamically adapting to varying execution context. Such a dynamic adaptation is particular...
Romain Rouvoy, Paolo Barone, Yun Ding, Frank Elias...
It is commonly agreed that a self-adaptive software system is one that can modify itself at run-time due to changes in the system, its requirements, or the environment in which it ...
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Robotics is a challenging domain that exhibits a clear need for self-adaptive capabilities, as self-adaptation offers the potential for robots to account for their unstable and unp...
To operate reliably in environments where interaction with an operator is infrequent or undesirable, an autonomous system should be capable of both determining how to achieve its ...
William Heaven, Daniel Sykes, Jeff Magee, Jeff Kra...
To deal with the increasing complexity of software systems and uncertainty of their environments, software engineers have turned to self-adaptivity. Self-adaptive systems are capab...
Yuriy Brun, Giovanna Di Marzo Serugendo, Cristina ...
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...