Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5 -GA [28], can solve GA-difficult problems by automati...
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
While many devices today increasingly have the ability to predict human activities, it is still difficult to build accurate personalized machine learning models. As users today wi...
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...