Many existing techniques for image restoration can be expressed in terms of minimizing a particular cost function. Iterative regularization methods are a novel variation on this th...
Abstract-- Identification of output error models from frequency domain data generally results in a non-convex optimization problem. A well-known method to approach the output error...
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...