Recent research has shown that while many complex networks follow a power-law distribution for their node degrees, it is not sufficient to model these networks based only on their...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
- A dynamical neural model that is strongly biologically motivated is applied to learning and retrieving binary patterns. This neural network, known as Freeman’s Ksets, is traine...
Abstract. As computer networks grow in size, both physically and geographically, more scalable solutions to network administration are becoming necessary. This need is amplified by...
Jacob W. Kallman, Pedrum Minaie, Jason Truppi, Ser...
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...