The problem of combining the ranked preferences of many experts is an old and surprisingly deep problem that has gained renewed importance in many machine learning, data mining, a...
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Al...
Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang, Xif...
In the context of machine learning from examples this paper deals with the problem of estimating the quality of attributes with and without dependencies among them. Kira and Rendel...
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...