Topic models such as aspect model or LDA have been shown as a promising approach for text modeling. Unlike many previous models that restrict each document to a single topic, topi...
We extend the "Sparse LDA" algorithm of [7] with new sparsity bounds on 2-class separability and efficient partitioned matrix inverse techniques leading to 1000-fold spe...
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...