High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
Abstract. We have developed a new semi-automated method for segmenting images of biological cells seeded at low density on tissue culture substrates, which we use to improve the ge...
Joe Chalfoun, Alden Dima, Adele P. Peskin, John T....
Much excitement has been generated by the success of stochastic local search procedures at finding solutions to large, very hard satisfiability problems. Many of the problems on wh...
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
Most text mining methods are based on representing documents using a vector space model, commonly known as a bag of word model, where each document is modeled as a linear vector r...
Rowena Chau, Ah Chung Tsoi, Markus Hagenbuchner, V...