The field of machine translation is almost as old as the modern digital computer. In 1949
Warren Weaver suggested that the problem be attacked with statistical methods and ideas from …

The application of kernel-based learning algorithms has, so far, largely been confined to
realvalued data and a few special data types, such as strings. In this paper we propose a …

We consider the problem of estimating the graph associated with a binary Ising Markov
random field. We describe a method based on ℓ 1 -regularized logistic regression, in which the …

Previous studies reported an association between elevated mean platelet volume (MPV)
and post-myocardial infarction mortality. This study explores the association between long-term …

… John Lafferty, Andrew McCallum, Fernando Pereira …

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, …

A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis
distance, Itakura-Saito distance and relative entropy, have been used for clustering. In this paper…

… do not model the dynamics of topic correlation, as was done for static models by Blei and
Lafferty (2006). … take n = 2J and J = 7. To be consistent with our earlier notation, we assume that …

… In this paper we develop the correlated topic model (CTM), where the topic proportions
exhibit correlation via the logistic normal distribution [J. Roy. Statist. … Consider two …

Language modeling approaches to information retrieval are attractive and promising because
they connect the problem of retrieval with that of language model estimation, which has …