We consider the problem of ordinal classification, in which a value set of the decision attribute (output, dependent variable) is finite and ordered. This problem shares some chara...
Krzysztof Dembczynski, Wojciech Kotlowski, Roman S...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Abstract-- This paper addresses the problem of traffic grooming in WDM rings in which all traffic emanates from a single node and all other nodes are destination nodes. This "...
Kevin Corcoran, Seth Flaxman, Mark Neyer, Peter Sc...
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
We consider a suboptimal solution path algorithm for the Support Vector Machine. The solution path algorithm is an effective tool for solving a sequence of a parametrized optimiz...