Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Abstract. This paper deals with the design of an API for building distributed parallel applications in C++ which embody strict multithreaded computations. The API is enhanced with ...
This paper describes PARDIS, a system containing explicit support for interoperability of PARallel DIStributed applications. PARDIS is based on the Common Object Request Broker Ar...
A new technique to parallelize loops with variable distance vectors is presented. The method extends previous methods in two ways. First, the present method makes it possible for ...
Abstract. We study bisimulation and minimization for weighted automata, relying on a geometrical representation of the model, linear weighted automata (lwa). In a lwa, the state-sp...