Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
This paper develops a practical method for image resolution enhancement. The method optimizes the spatially constrained Wiener filter for an efficiently parameterized model of the...
Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
Proposed and developed is a service composition framework for decision-making under uncertainty, which is applicable to stochastic optimization of supply chains. Also developed is ...