We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
This paper describes an incremental parser and an unsupervised learning algorithm for inducing this parser from plain text. The parser uses a representation for syntactic structur...
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Motivated by the slow learning properties of multilayer perceptrons (MLPs) which utilize computationally intensive training algorithms, such as the backpropagation learning algorit...
This study wishes to describe some of the key components of an art educational domain entitled ground<c>, which is being developed specifically for three dimensional online ...