We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
The widespread distribution and availability of smallscale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such examp...
With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different typ...
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...