This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
In this paper, we present a novel method for dynamic terrain in battlefield and an efficient plan to simulate crater in the battle. We explore a few methods for dynamic terrain sur...
Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...