Large collaborative datasets offer the challenging opportunity of creating systems capable of extracting knowledge in the presence of noisy data. In this work we explore the abili...
Emily Moxley, Jim Kleban, Jiejun Xu, B. S. Manjuna...
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
The trend towards multicore processors and graphic processing units is increasing the need for software that can take advantage of parallelism. Writing correct parallel programs u...
Decision trees are a widely used knowledge representation in machine learning. However, one of their main drawbacks is the inherent replication of isomorphic subtrees, as a result...
Christophe Mues, Bart Baesens, Craig M. Files, Jan...
In this paper, we describe PSE (Postmortem Symbolic Evaluation), a static analysis algorithm that can be used by programmers to diagnose software failures. The algorithm requires ...
Roman Manevich, Manu Sridharan, Stephen Adams, Man...