In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
Most decision tree classifiers are designed to keep class histograms for single attributes, and to select a particular attribute for the next split using said histograms. In this ...
In forestry, it is important to be able to accurately determine the volume of timber in a harvesting site and the products that could potentially be produced from that timber. We d...
Conor Nugent, Derek G. Bridge, Glen Murphy, Bernt-...
—A sequential decoder for linear block codes that performs maximum-likelihood soft-decision decoding is described. The decoder uses a metric computed from a lower bound on the co...
Besides search, complete inference methods can also be used to solve soft constraint problems. Their main drawback is the high spatial complexity. To improve its practical usage, w...