Attempts to extract logical rules from data often lead to large sets of classification rules that need to be pruned. Training two classifiers, the C4.5 decision tree and the Non-Ne...
Karol Grudzinski, Marek Grochowski, Wlodzislaw Duc...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
We study the problem of maximizing the broadcast rate in peer-to-peer (P2P) systems under node degree bounds, i.e., the number of neighbors a node can simultaneously connect to is ...
In an important recent paper, Yedidia, Freeman, and Weiss [11] showed that there is a close connection between the belief propagation algorithm for probabilistic inference and the...
Jonathan S. Yedidia, William T. Freeman, Yair Weis...
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...