This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Reservoir sampling is a well-known technique for sequential random sampling over data streams. Conventional reservoir sampling assumes a fixed-size reservoir. There are situation...
Mohammed Al-Kateb, Byung Suk Lee, Xiaoyang Sean Wa...
This study proposes a novel forecasting approach – an adaptive smoothing neural network (ASNN) – to predict foreign exchange rates. In this new model, adaptive smoothing techni...
In this paper we describe a stochastic local search (SLS) procedure for finding models of satisfiable propositional formulae. This new algorithm, gNovelty+ , draws on the features...
Duc Nghia Pham, John Thornton, Charles Gretton, Ab...