In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Earlier work has demonstrated the effectiveness of in-network data aggregation in order to minimize the amount of messages exchanged during continuous queries in large sensor netwo...
Antonios Deligiannakis, Yannis Kotidis, Nick Rouss...
Compared are different methods for evaluation of formulas expressing microprocessor correctness in the logic of Equality with Uninterpreted Functions and Memories (EUFM) by transl...