— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Abstract— We investigate a widely popular Least-RecentlyUsed (LRU) cache replacement algorithm with semi-Markov modulated requests. Semi-Markov processes provide the flexibility...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
We evaluate response times, in N-user collaborations, of the popular centralized (client-server) and replicated (peer-to-peer) architectures, and a hybrid architecture in which ea...
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...