We present an evolutionary methodology that explores the evolution of network topology when a uniform growth of the network traffic is considered. The network redesign problem is ...
In this paper, we introduce a rotating interrogation technique for sensor networks called Whirlpool. Whirlpool provides opportunities to optimize data delivery in time-critical mo...
Divyasheel Sharma, Vladimir Zadorozhny, Panos K. C...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...