This paper describes Slepian-Wolf codes based on overlapped quasi-arithmetic codes, where overlapping allows lossy compression of the source below its entropy. In the context of s...
Xavier Artigas, Simon Malinowski, Christine Guille...
An anytime algorithm is capable of returning a response to the given task at essentially any time; typically the quality of the response improves as the time increases. Here, we c...
In this paper we analyze the most popular evaluation metrics for separate-and-conquer rule learning algorithms. Our results show that all commonly used heuristics, including accur...
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
We present Nodeinfo, an unsupervised algorithm for anomaly detection in system logs. We demonstrate Nodeinfo’s effectiveness on data from four of the world’s most powerful sup...