A persistent concern of wireless sensors is the power consumption required for communication, which presents a significant adoption hurdle for practical ubiquitous computing appli...
Gabe Cohn, Erich P. Stuntebeck, Jagdish Pandey, Br...
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
We present recent results from the LCDM3 collaboration between UIUC Astronomy and NCSA to deploy supercomputing cluster resources and machine learning algorithms for the mining of ...
Nicholas M. Ball, Robert J. Brunner, Adam D. Myers
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...