This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of syst...
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...
Whether a given nonlinear solver can reach a feasible point for a set of nonlinear constraints depends heavily on the initial point provided. We develop a range of computationally...
Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techn...
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...