A real-time AI system in the real world needs to monitor an immense volume of data. To do this, the system must filter out much of the incoming data. However, it must remain re ...
An effective method for reducing the effect of load latency in modern processors is data prefetching. One form of data prefetching, stream buffers, has been shown to be particular...
This paper considers the problem of change detection using local distributed eigen monitoring algorithms for next generation of astronomy petascale data pipelines such as the Larg...
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the architectural framework of the larger ap...