The Data Diffusion Machine is a scalable virtual shared memory architecture. A hierarchical network is used to ensure that all data can be located in a time bounded by O(logp), wh...
Henk L. Muller, Paul W. A. Stallard, David H. D. W...
Parallel software for solving the quadratic program arising in training support vector machines for classification problems is introduced. The software implements an iterative dec...
Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven t...
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...