Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fie...
V. Chandrasekaran, Jason K. Johnson, Alan S. Wills...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
: Nonnegative matrix approximation (NNMA) is a popular matrix decomposition technique that has proven to be useful across a diverse variety of fields with applications ranging from...
In this paper, we develop a new language construct to address one of the pitfalls of parallel programming: precise handling of events across parallel components. The construct, te...
William Thies, Michal Karczmarek, Janis Sermulins,...
Abstract. Measurement of activation rates in cardiac electrograms is commonly done though estimating the frequency of the sinusoid with the greatest power. This frequency, commonly...