This paper examines the costs and potential benefits of long-term prefetching for content distribution. In traditional short-term prefetching, caches use recent access history to ...
Arun Venkataramani, Praveen Yalagandula, Ravi Kokk...
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
The lack of automation associated with network operations in general and network configuration management in particular, is widely recognized as a significant contributing factor ...
Xu Chen, Zhuoqing Morley Mao, Jacobus E. van der M...
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
: The contribution concerns the design of a generalised functional-link neural network with internal dynamics and its applicability to system identification by means of multi-input...