This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
A key question regarding the future of the semantic web is “how will we acquire structured information to populate the semantic web on a vast scale?” One approach is to enter t...
Tom M. Mitchell, Justin Betteridge, Andrew Carlson...
Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...
Large repositories of source code create new challenges and opportunities for statistical machine learning. Here we first develop Sourcerer, an infrastructure for the automated c...
Erik Linstead, Paul Rigor, Sushil Krishna Bajracha...