Artificial neural networks (ANNs) have been successfully applied to solve a variety of classification and function approximation problems. Although ANNs can generally predict bett...
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
—Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such ...
As CMOS feature sizes venture deep into the nanometer regime, wearout mechanisms including negative-bias temperature instability and timedependent dielectric breakdown can severely...
Shuguang Feng, Shantanu Gupta, Amin Ansari, Scott ...
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...