In real-world domains a concept to be learned may be unwieldy and the environment may be less than ideal. One combination of difficulties occurs if the concept is probabilistic an...
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Abstract— Prefetching is a widely used technique in modern data storage systems. We study the most widely used class of prefetching algorithms known as sequential prefetching. Th...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...