A recent report by the National Research Council (NRC) declares neural networks “hold the most promise for providing powerful learning models”. While some researchers have expe...
Amy E. Henninger, Avelino J. Gonzalez, Michael Geo...
Several features such as reconfiguration, voltage and frequency scaling, low-power operating states, duty-cycling, etc. are exploited for latency and energy efficient application ...
Pervasive and ad hoc computing applications are frequently deployed in dynamic networks. Due to mobility of the computing nodes, their unreliability, or a limited communication ra...
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Abstract. This paper reviews recent developments in our project that are focused on dynamic data-driven methods for efficient and reliable simulation based optimization, which may...