In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three ma...
Shawn Martin, George Davidson, Elebeoba E. May, Je...
This paper is devoted to the analysis of network approximation in the framework of approximation and regularization theory. It is shown that training neural networks and similar n...
—Anonymous wireless networking is studied when an adversary monitors the transmission timing of an unknown subset of the network nodes. For a desired quality of service (QoS), as...
We propose, and justify, an economic theory to guide memory system design, operation, and analysis. Our theory treats memory random-access latency, and its cost per installed mega...
This paper presents a wavelet neural-network for learning and approximation of chaotic time series. Wavelet-networks are inspired by both feed-forward neural networks and the theo...