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» Evaluating algorithms that learn from data streams
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IJCAI
1989
15 years 7 months ago
A Study of Empirical Learning for an Involved Problem
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...
Larry A. Rendell
GRC
2010
IEEE
15 years 7 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
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...
Lili Zhang, Erzsébet Merényi
FAST
2007
15 years 8 months ago
AMP: Adaptive Multi-stream Prefetching in a Shared Cache
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...
Binny S. Gill, Luis Angel D. Bathen
NIPS
2003
15 years 8 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
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...
Stuart Andrews, Thomas Hofmann
UAI
1997
15 years 8 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
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...