This paper gives an overview of recent work on machine models for processing massive amounts of data. The main focus is on generalizations of the classical data stream model where...
There is growing interest in run-time detection as parallel and distributed systems grow larger and more complex. This work targets run-time analysis of complex, interactive scien...
Many real-time applications, such as traffic control systems, surveillance systems and health monitoring systems, need to operate on continuous unbounded streams of data. These ap...
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
: In this paper, we present a novel method for fast data-driven construction of regression trees from temporal datasets including continuous data streams. The proposed Mean Output ...