Empirical studies of the variation in debt ratios across firms have used statistical models singularly to analyze the important determinants of capital structure. Researchers, how...
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
We propose a new technique for hardware synthesis from higherorder functional languages with imperative features based on Reynolds's Syntactic Control of Interference. The re...
Recently, generative probabilistic modeling principles were extended to visualization of structured data types, such as sequences. The models are formulated as constrained mixture...
A new platform for reconfigurable computing has an object-based programming model, with architecture, silicon and tools designed to faithfully realize this model. The platform is ...