Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
In underdetermined blind source separation problems, it is common practice to exploit the underlying sparsity of the sources for demixing. In this work, we propose two sparse decom...
Abstract— This paper proposes a multiple robot control algorithm to approach the problem of patrolling an open or closed line. The algorithm is fully decentralized, i.e., no comm...
Alessandro Marino, Lynne E. Parker, Gianluca Anton...
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has become an important pro...
This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demons...
Helder Knidel, Leandro Nunes de Castro, Fernando J...