Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
This paper presents a novel approach for knowledge mining from a sparse and repeated measures dataset. Genetic programming based symbolic regression is employed to generate multip...
Katya Vladislavleva, Kalyan Veeramachaneni, Matt B...
We develop a consistent mutable replication extension for NFSv4 tuned to meet the rigorous demands of largescale data sharing in global collaborations. The system uses a hierarchi...
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
— An effectively designed and efficiently used memory hierarchy, composed of scratch-pads or cache, is seen today as the key to obtaining energy and performance gains in data-do...