In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
Andreas Krause, H. Brendan McMahan, Carlos Guestri...
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Neural-symbolic systems are hybrid systems that integrate symbolic logic and neural networks. The goal of neural-symbolic integration is to benefit from the combination of feature...
Forecasting of wave height is necessary in a large number of ocean coastal activities. Recently, neural networks are used for prediction and approximation of wave heights in sea a...
Traditional methods for ATR Automatic Target Recognition use infrared IR sensors for detecting heat emanating fromtargets. IR-based ATR techniques are susceptible to sensor-in...