A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each si...
In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently. In XAR-Miner, raw data in the XML document are first preprocessed to transf...
This paper describes the issues and challenges for real-time knowledge discovery and then discusses approaches and challenges for real-time data mining and stream mining. Our goal...
Bhavani M. Thuraisingham, Latifur Khan, Murat Kant...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...